{
 "_meta": {
  "title": "Background incidence rates for observed-vs-expected vaccine safety analysis",
  "compiled": "2026-10-09",
  "method": "Every value was read from a source document actually downloaded and opened (PMC HTML, PDF text, or figure image). Nothing estimated or interpolated. Where the source unit differed (per 1,000 PY, per million PY, per 100,000 person-months), a pure unit conversion was applied and stated in notes.",
  "units": "rate_per_100k_py unless the row has rate_per_100k_live_births (SIDS) or rate_per_million_doses (vaccine-triggered anaphylaxis). Several literature rates are 'per 100,000 population per year'; these are treated as approximately per 100k PY and flagged in notes.",
  "caveats": [
   "Li 2021 intervals are 95% prediction intervals across databases, not confidence intervals.",
   "Gubernot 2021 is a secondary compilation; the primary study is named in location_in_source.",
   "Code-based rates (Li, Willame, Payne, Johnson) are not chart-validated and generally exceed validated (Brighton-level) rates; compare like with like.",
   "Willame values are age-standardised European pools; do not apply them directly to a US age structure."
  ],
  "sources": [
   "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries) 10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU) 10.1016/j.vaccine.2022.11.031; PMC9678835",
   "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates) 10.1016/j.vaccine.2021.05.016; PMC8118666",
   "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety) 10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC) 10.1002/rth2.12682; PMC8901465",
   "Tate JE et al. 2008 Pediatrics 10.1542/peds.2007-1590; PMC2680116",
   "Christensen KJ et al. 2021 Acta Neurol Scand 10.1111/ane.13420; PMC8178233",
   "Johnson BH et al. 2015 BMC Infect Dis 10.1186/s12879-015-1262-8; PMC4636742",
   "McNeil MM et al. 2016 J Allergy Clin Immunol (Vaccine Safety Datalink) 10.1016/j.jaci.2015.07.048; PMID 26452420; PMC4783279",
   "Ely DM, Driscoll AK. 2021 National Vital Statistics Reports 70(14): Infant Mortality in the United States, 2019"
  ]
 },
 "rates": [
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 4,
   "ci_low": 2,
   "ci_high": 9,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 4,
   "ci_low": 1,
   "ci_high": 12,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 18,
   "ci_low": 4,
   "ci_high": 86,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 83,
   "ci_low": 11,
   "ci_high": 617,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 217,
   "ci_low": 25,
   "ci_high": 1882,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 413,
   "ci_low": 77,
   "ci_high": 2198,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 874,
   "ci_low": 197,
   "ci_high": 3884,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 1523,
   "ci_low": 320,
   "ci_high": 7239,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 6,
   "ci_low": 2,
   "ci_high": 20,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 5,
   "ci_low": 2,
   "ci_high": 10,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 17,
   "ci_low": 4,
   "ci_high": 75,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 119,
   "ci_low": 21,
   "ci_high": 664,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 370,
   "ci_low": 67,
   "ci_high": 2046,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 612,
   "ci_low": 145,
   "ci_high": 2578,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 1063,
   "ci_low": 242,
   "ci_high": 4662,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Non-haemorrhagic (ischaemic) stroke",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 1495,
   "ci_low": 260,
   "ci_high": 8607,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Non-haemorrhagic' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 6,
   "ci_low": 1,
   "ci_high": 49,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 54,
   "ci_low": 7,
   "ci_high": 430,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 171,
   "ci_low": 24,
   "ci_high": 1235,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 312,
   "ci_low": 76,
   "ci_high": 1280,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 617,
   "ci_low": 184,
   "ci_high": 2069,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 1144,
   "ci_low": 313,
   "ci_high": 4184,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 1,
   "ci_low": 1,
   "ci_high": 1,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 16,
   "ci_low": 4,
   "ci_high": 72,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 172,
   "ci_low": 40,
   "ci_high": 740,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 467,
   "ci_low": 135,
   "ci_high": 1611,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 653,
   "ci_low": 214,
   "ci_high": 1994,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 934,
   "ci_low": 290,
   "ci_high": 3013,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 1514,
   "ci_low": 356,
   "ci_high": 6432,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Acute myocardial infarction' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 12,
   "ci_low": 3,
   "ci_high": 50,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 18,
   "ci_low": 8,
   "ci_high": 40,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 140,
   "ci_low": 66,
   "ci_high": 298,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 306,
   "ci_low": 117,
   "ci_high": 797,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 428,
   "ci_low": 150,
   "ci_high": 1224,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 683,
   "ci_low": 257,
   "ci_high": 1820,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 975,
   "ci_low": 360,
   "ci_high": 2642,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 1206,
   "ci_low": 407,
   "ci_high": 3572,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 14,
   "ci_low": 4,
   "ci_high": 55,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 14,
   "ci_low": 6,
   "ci_high": 32,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 80,
   "ci_low": 28,
   "ci_high": 228,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 272,
   "ci_low": 88,
   "ci_high": 836,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 499,
   "ci_low": 194,
   "ci_high": 1289,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 695,
   "ci_low": 250,
   "ci_high": 1931,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 831,
   "ci_low": 254,
   "ci_high": 2720,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Deep vein thrombosis",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 1003,
   "ci_low": 278,
   "ci_high": 3616,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Deep vein thrombosis' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 7,
   "ci_low": 2,
   "ci_high": 28,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 5,
   "ci_low": 2,
   "ci_high": 16,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 13,
   "ci_low": 4,
   "ci_high": 47,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 36,
   "ci_low": 7,
   "ci_high": 175,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 77,
   "ci_low": 15,
   "ci_high": 389,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 124,
   "ci_low": 29,
   "ci_high": 527,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 249,
   "ci_low": 56,
   "ci_high": 1108,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 412,
   "ci_low": 85,
   "ci_high": 1986,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 8,
   "ci_low": 2,
   "ci_high": 43,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 8,
   "ci_low": 3,
   "ci_high": 24,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 19,
   "ci_low": 5,
   "ci_high": 76,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 51,
   "ci_low": 10,
   "ci_high": 268,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 115,
   "ci_low": 23,
   "ci_high": 562,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 178,
   "ci_low": 49,
   "ci_high": 650,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 312,
   "ci_low": 73,
   "ci_high": 1340,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 506,
   "ci_low": 86,
   "ci_high": 2961,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Haemorrhagic stroke' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 36,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 3,
   "ci_low": 1,
   "ci_high": 13,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 38,
   "ci_low": 11,
   "ci_high": 124,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 81,
   "ci_low": 21,
   "ci_high": 309,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 125,
   "ci_low": 33,
   "ci_high": 470,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 217,
   "ci_low": 77,
   "ci_high": 611,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 358,
   "ci_low": 135,
   "ci_high": 951,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 427,
   "ci_low": 154,
   "ci_high": 1184,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 24,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 2,
   "ci_low": null,
   "ci_high": 12,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 20,
   "ci_low": 5,
   "ci_high": 80,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 80,
   "ci_low": 20,
   "ci_high": 318,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 171,
   "ci_low": 59,
   "ci_high": 497,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 256,
   "ci_low": 96,
   "ci_high": 683,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 349,
   "ci_low": 119,
   "ci_high": 1030,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Pulmonary embolism",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 398,
   "ci_low": 124,
   "ci_high": 1277,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Pulmonary embolism' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 32,
   "ci_low": 12,
   "ci_high": 84,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 154,
   "ci_low": 55,
   "ci_high": 430,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 134,
   "ci_low": 69,
   "ci_high": 260,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 85,
   "ci_low": 42,
   "ci_high": 172,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 66,
   "ci_low": 28,
   "ci_high": 156,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 53,
   "ci_low": 20,
   "ci_high": 143,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 40,
   "ci_low": 13,
   "ci_high": 124,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 35,
   "ci_low": 12,
   "ci_high": 98,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 38,
   "ci_low": 17,
   "ci_high": 85,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 194,
   "ci_low": 101,
   "ci_high": 372,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 146,
   "ci_low": 81,
   "ci_high": 266,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 88,
   "ci_low": 49,
   "ci_high": 159,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 65,
   "ci_low": 32,
   "ci_high": 132,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 57,
   "ci_low": 23,
   "ci_high": 144,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 47,
   "ci_low": 15,
   "ci_high": 152,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Appendicitis",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 45,
   "ci_low": 14,
   "ci_high": 143,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Appendicitis' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 15,
   "ci_low": 9,
   "ci_high": 27,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 25,
   "ci_low": 12,
   "ci_high": 51,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 44,
   "ci_low": 23,
   "ci_high": 84,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 61,
   "ci_low": 26,
   "ci_high": 140,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 76,
   "ci_low": 31,
   "ci_high": 184,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 86,
   "ci_low": 29,
   "ci_high": 256,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 101,
   "ci_low": 31,
   "ci_high": 330,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 92,
   "ci_low": 31,
   "ci_high": 274,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 15,
   "ci_low": 10,
   "ci_high": 24,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 21,
   "ci_low": 13,
   "ci_high": 34,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 43,
   "ci_low": 29,
   "ci_high": 64,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 68,
   "ci_low": 37,
   "ci_high": 125,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 86,
   "ci_low": 43,
   "ci_high": 172,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 94,
   "ci_low": 35,
   "ci_high": 252,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 92,
   "ci_low": 29,
   "ci_high": 291,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 100,
   "ci_low": 34,
   "ci_high": 292,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Bell's palsy' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 49,
   "ci_low": 16,
   "ci_high": 150,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 50,
   "ci_low": 16,
   "ci_high": 154,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 39,
   "ci_low": 16,
   "ci_high": 95,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 34,
   "ci_low": 13,
   "ci_high": 91,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 35,
   "ci_low": 14,
   "ci_high": 85,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 29,
   "ci_low": 11,
   "ci_high": 76,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 23,
   "ci_low": 7,
   "ci_high": 73,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 12,
   "ci_low": 4,
   "ci_high": 36,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 74,
   "ci_low": 26,
   "ci_high": 209,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 56,
   "ci_low": 18,
   "ci_high": 175,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 29,
   "ci_low": 14,
   "ci_high": 63,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 24,
   "ci_low": 11,
   "ci_high": 53,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 25,
   "ci_low": 11,
   "ci_high": 53,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 24,
   "ci_low": 9,
   "ci_high": 68,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 18,
   "ci_low": 7,
   "ci_high": 49,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 10,
   "ci_low": 2,
   "ci_high": 50,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Anaphylaxis' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 12,
   "ci_low": 8,
   "ci_high": 19,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 9,
   "ci_low": 4,
   "ci_high": 21,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 14,
   "ci_low": 6,
   "ci_high": 36,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 15,
   "ci_low": 5,
   "ci_high": 43,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 18,
   "ci_low": 6,
   "ci_high": 53,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 25,
   "ci_low": 8,
   "ci_high": 82,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 30,
   "ci_low": 8,
   "ci_high": 110,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 36,
   "ci_low": 11,
   "ci_high": 118,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 17,
   "ci_low": 12,
   "ci_high": 23,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 8,
   "ci_low": 3,
   "ci_high": 19,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 8,
   "ci_low": 2,
   "ci_high": 23,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 10,
   "ci_low": 3,
   "ci_high": 35,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 19,
   "ci_low": 6,
   "ci_high": 57,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 30,
   "ci_low": 9,
   "ci_high": 105,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 41,
   "ci_low": 10,
   "ci_high": 170,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 56,
   "ci_low": 15,
   "ci_high": 210,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Immune thrombocytopenia' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 6,
   "ci_low": 1,
   "ci_high": 25,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 7,
   "ci_low": 2,
   "ci_high": 21,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 16,
   "ci_low": 8,
   "ci_high": 32,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 22,
   "ci_low": 9,
   "ci_high": 53,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 31,
   "ci_low": 13,
   "ci_high": 72,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 35,
   "ci_low": 12,
   "ci_high": 97,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 39,
   "ci_low": 11,
   "ci_high": 138,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 34,
   "ci_low": 8,
   "ci_high": 143,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 7,
   "ci_low": 1,
   "ci_high": 32,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 11,
   "ci_low": 5,
   "ci_high": 24,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 37,
   "ci_low": 16,
   "ci_high": 88,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 37,
   "ci_low": 16,
   "ci_high": 87,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 45,
   "ci_low": 20,
   "ci_high": 102,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 49,
   "ci_low": 17,
   "ci_high": 139,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 54,
   "ci_low": 15,
   "ci_high": 193,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 41,
   "ci_low": 9,
   "ci_high": 193,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Myocarditis or pericarditis' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 5,
   "ci_low": 2,
   "ci_high": 15,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 5,
   "ci_low": 2,
   "ci_high": 16,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 5,
   "ci_low": 2,
   "ci_high": 19,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 6,
   "ci_low": 1,
   "ci_high": 44,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 9,
   "ci_low": 1,
   "ci_high": 61,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 11,
   "ci_low": 2,
   "ci_high": 62,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 12,
   "ci_low": 2,
   "ci_high": 77,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 14,
   "ci_low": 2,
   "ci_high": 100,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 5,
   "ci_low": 2,
   "ci_high": 12,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 5,
   "ci_low": 2,
   "ci_high": 14,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 5,
   "ci_low": 2,
   "ci_high": 17,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 7,
   "ci_low": 1,
   "ci_high": 55,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 12,
   "ci_low": 3,
   "ci_high": 58,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 16,
   "ci_low": 3,
   "ci_high": 73,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 18,
   "ci_low": 3,
   "ci_high": 101,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Encephalomyelitis (incl. ADEM)",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 16,
   "ci_low": 1,
   "ci_high": 180,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Encephalomyelitis' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype is encephalomyelitis broadly (includes ADEM); inpatient record required."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 5,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution. Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 7,
   "ci_low": 3,
   "ci_high": 17,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 15,
   "ci_low": 4,
   "ci_high": 52,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 11,
   "ci_low": 2,
   "ci_high": 55,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 9,
   "ci_low": 2,
   "ci_high": 42,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 10,
   "ci_low": 2,
   "ci_high": 46,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 8,
   "ci_low": 1,
   "ci_high": 49,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 9,
   "ci_low": 2,
   "ci_high": 42,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 5,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution. Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 6,
   "ci_low": 2,
   "ci_high": 18,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 13,
   "ci_low": 4,
   "ci_high": 40,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 10,
   "ci_low": 2,
   "ci_high": 47,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 11,
   "ci_low": 3,
   "ci_high": 44,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 10,
   "ci_low": 2,
   "ci_high": 50,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 10,
   "ci_low": 2,
   "ci_high": 68,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 10,
   "ci_low": 2,
   "ci_high": 60,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Narcolepsy' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Code-based narcolepsy rates far exceed chart-validated estimates (e.g. Silber 2002, Olmsted County, 1.37/100k). Use with caution."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 8,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position. Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 2,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position. Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 3,
   "ci_low": 1,
   "ci_high": 5,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 3,
   "ci_low": 1,
   "ci_high": 11,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 5,
   "ci_low": 1,
   "ci_high": 18,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 6,
   "ci_low": 2,
   "ci_high": 19,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 6,
   "ci_low": 3,
   "ci_high": 16,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 7,
   "ci_low": 2,
   "ci_high": 22,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 2,
   "ci_low": null,
   "ci_high": 18,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position. Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 3,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position. Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 2,
   "ci_low": 1,
   "ci_high": 4,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 4,
   "ci_low": 2,
   "ci_high": 7,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 7,
   "ci_low": 4,
   "ci_high": 14,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 8,
   "ci_low": 3,
   "ci_high": 25,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 11,
   "ci_low": 3,
   "ci_high": 40,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 12,
   "ci_low": 2,
   "ci_high": 68,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Guillain-Barre syndrome' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Phenotype required an inpatient diagnosis in primary position."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "1-5",
   "sex": "female",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 3,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Female, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "6-17",
   "sex": "female",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 3,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Female, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "18-34",
   "sex": "female",
   "rate_per_100k_py": 3,
   "ci_low": 1,
   "ci_high": 8,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Female, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "35-54",
   "sex": "female",
   "rate_per_100k_py": 4,
   "ci_low": 1,
   "ci_high": 12,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Female, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "55-64",
   "sex": "female",
   "rate_per_100k_py": 4,
   "ci_low": 2,
   "ci_high": 13,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Female, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "65-74",
   "sex": "female",
   "rate_per_100k_py": 4,
   "ci_low": 2,
   "ci_high": 13,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Female, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "75-84",
   "sex": "female",
   "rate_per_100k_py": 4,
   "ci_low": 1,
   "ci_high": 11,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Female, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "85+",
   "sex": "female",
   "rate_per_100k_py": 2,
   "ci_low": 1,
   "ci_high": 9,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Female, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "1-5",
   "sex": "male",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 2,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Male, column 1-5 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "6-17",
   "sex": "male",
   "rate_per_100k_py": 1,
   "ci_low": null,
   "ci_high": 3,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Male, column 6-17 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3). Lower prediction bound printed as '<1'."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "18-34",
   "sex": "male",
   "rate_per_100k_py": 2,
   "ci_low": 1,
   "ci_high": 6,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Male, column 18-34 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "35-54",
   "sex": "male",
   "rate_per_100k_py": 3,
   "ci_low": 1,
   "ci_high": 10,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Male, column 35-54 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "55-64",
   "sex": "male",
   "rate_per_100k_py": 4,
   "ci_low": 1,
   "ci_high": 10,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Male, column 55-64 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "65-74",
   "sex": "male",
   "rate_per_100k_py": 4,
   "ci_low": 1,
   "ci_high": 11,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Male, column 65-74 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 4,
   "ci_low": 1,
   "ci_high": 13,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Male, column 75-84 years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "85+",
   "sex": "male",
   "rate_per_100k_py": 4,
   "ci_low": 1,
   "ci_high": 11,
   "country": "Pooled: Australia, France, Germany, Japan, Netherlands, Spain, UK, US (random-effects meta-analysis)",
   "years": "Cohorts indexed 1 Jan 2017/2018/2019 (pre-pandemic)",
   "source": "Li X et al. 2021 BMJ (OHDSI network, 13 databases, 8 countries)",
   "doi_or_pmid": "10.1136/bmj.n1435; PMID 35727911; PMC8193077",
   "location_in_source": "Figure 3, row 'Transverse myelitis' / Male, column 85+ years",
   "notes": "Pooled meta-analytic rate. ci_low/ci_high are 95% PREDICTION intervals (not CIs); wide because of between-database heterogeneity. Diagnosis-code phenotypes, not chart-validated. Read from Figure 3 (PMC image lix065802.f3)."
  },
  {
   "condition": "Acute disseminated encephalomyelitis (ADEM)",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 0.33,
   "ci_low": 0.06,
   "ci_high": 0.59,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Acute disseminated encephalomyelitis', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 3.21,
   "ci_low": 1.0,
   "ci_high": 4.42,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Guillain-Barre syndrome', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 1.58,
   "ci_low": 0.91,
   "ci_high": 2.26,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Narcolepsy', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Thrombocytopenia (all-cause, incl. ITP)",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 92.09,
   "ci_low": 42.47,
   "ci_high": 141.71,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Thrombocytopenia', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially. Thrombocytopenia of any cause, not ITP specifically."
  },
  {
   "condition": "Myocarditis",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 3.18,
   "ci_low": 1.73,
   "ci_high": 4.62,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Myocarditis', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Myocarditis or pericarditis",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 20.63,
   "ci_low": 12.91,
   "ci_high": 28.35,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Myocarditis or pericarditis', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 0.85,
   "ci_low": 0.53,
   "ci_high": 1.17,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Cerebral venous sinus thrombosis', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Haemorrhagic stroke",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 43.58,
   "ci_low": 26.44,
   "ci_high": 60.73,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Haemorrhagic stroke', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Ischemic stroke",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 229.29,
   "ci_low": 159.11,
   "ci_high": 299.46,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Ischemic stroke', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Venous thromboembolism",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 229.67,
   "ci_low": 207.52,
   "ci_high": 251.83,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Venous thromboembolism', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Generalized convulsion (all ages, all causes)",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 152.35,
   "ci_low": 78.67,
   "ci_high": 226.02,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Generalized convulsion', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially. Generalized convulsion = all seizures at all ages, NOT febrile seizures in children."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 0.48,
   "ci_low": 0.23,
   "ci_high": 0.72,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Transverse myelitis', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 14.17,
   "ci_low": 7.46,
   "ci_high": 20.87,
   "country": "Pooled Europe (Denmark, France, Germany, Italy, Spain, Netherlands, UK; 10 databases)",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Anaphylaxis', column 'GP & IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition. Value is the 'GP & IN-OUTPATIENT' column (FISABIO and BIFAP/SIDIAP/PHARMO subpopulations, i.e. databases with both GP and hospital records). Other provenance columns differ substantially."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 3.33,
   "ci_low": 2.48,
   "ci_high": 4.17,
   "country": "Denmark registries + France SNDS",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'Guillain Barre Syndrome', column 'IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition; IN-OUTPATIENT databases."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 2.04,
   "ci_low": 0.04,
   "ci_high": 4.04,
   "country": "Denmark registries + France SNDS",
   "years": "2017-2019 (Danish registries 2010-2013; GePaRD 2014-2017)",
   "source": "Willame C et al. 2023 Vaccine (ACCESS project, EMA-funded, VAC4EU)",
   "doi_or_pmid": "10.1016/j.vaccine.2022.11.031; PMC9678835",
   "location_in_source": "Table 3, row 'CVST', column 'IN-OUTPATIENT'",
   "notes": "Age-standardised pooled IR, narrow definition; IN-OUTPATIENT databases."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "all ages (age-standardised)",
   "sex": "all",
   "rate_per_100k_py": 1.72,
   "ci_low": null,
   "ci_high": null,
   "country": "US (VSD cohort)",
   "years": "2000-2009",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, GBS paragraph 1 (ref 12: Shui IM et al. Neuroepidemiology 2012)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "all ages (age-standardised)",
   "sex": "female",
   "rate_per_100k_py": 1.45,
   "ci_low": null,
   "ci_high": null,
   "country": "US (VSD cohort)",
   "years": "2000-2009",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, GBS paragraph 1 (ref 12)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "all ages (age-standardised)",
   "sex": "male",
   "rate_per_100k_py": 2.04,
   "ci_low": null,
   "ci_high": null,
   "country": "US (VSD cohort)",
   "years": "2000-2009",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, GBS paragraph 1 (ref 12)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "0-9",
   "sex": "all",
   "rate_per_100k_py": 0.62,
   "ci_low": null,
   "ci_high": null,
   "country": "International (meta-analysis)",
   "years": "Studies 1966-2009",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, GBS paragraph 1 (ref 11: Sejvar JJ et al. Neuroepidemiology 2011)",
   "notes": "Secondary compilation; primary study named in location_in_source. Rises about 20% per 10-year increase in age."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "80-89",
   "sex": "all",
   "rate_per_100k_py": 2.66,
   "ci_low": null,
   "ci_high": null,
   "country": "International (meta-analysis)",
   "years": "Studies 1966-2009",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, GBS paragraph 1 (ref 11)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_100k_py": 0.949,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN; REP)",
   "years": "2003-2016",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, TM paragraph (ref 29: Sechi E et al. Neurology 2019)",
   "notes": "Secondary compilation; primary study named in location_in_source. Source gives 9.49 per million PY; divided by 10 (unit conversion only)."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "all ages",
   "sex": "male",
   "rate_per_100k_py": 0.715,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "2003-2016",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, TM paragraph (ref 29)",
   "notes": "Secondary compilation; primary study named in location_in_source. Source gives 7.15 per million PY; /10."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "all ages",
   "sex": "female",
   "rate_per_100k_py": 1.174,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "2003-2016",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, TM paragraph (ref 29)",
   "notes": "Secondary compilation; primary study named in location_in_source. Source gives 11.74 per million PY; /10."
  },
  {
   "condition": "Acute disseminated encephalomyelitis (ADEM)",
   "age_band": "0-18 (hospitalization)",
   "sex": "all",
   "rate_per_100k_py": 0.5,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Nationwide Inpatient Sample)",
   "years": "2006-2014",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ADEM paragraph; Table 2 (ref 35: Bhatt P et al.)",
   "notes": "Secondary compilation; primary study named in location_in_source. Hospitalization rate per 100,000 children (annual; approximates per 100k PY)."
  },
  {
   "condition": "Acute disseminated encephalomyelitis (ADEM)",
   "age_band": "<20",
   "sex": "all",
   "rate_per_100k_py": 0.4,
   "ci_low": null,
   "ci_high": null,
   "country": "US (San Diego, CA)",
   "years": "1991-2000",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ADEM paragraph; Table 2 (ref 36: Leake JA et al.)",
   "notes": "Secondary compilation; primary study named in location_in_source. Per 100,000 per year."
  },
  {
   "condition": "Acute disseminated encephalomyelitis (ADEM)",
   "age_band": "0-4",
   "sex": "all",
   "rate_per_100k_py": 0.6,
   "ci_low": null,
   "ci_high": null,
   "country": "US (San Diego, CA)",
   "years": "1991-2000",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ADEM paragraph (ref 36)",
   "notes": "Secondary compilation; primary study named in location_in_source. Per 100,000 per year."
  },
  {
   "condition": "Acute disseminated encephalomyelitis (ADEM)",
   "age_band": "5-9",
   "sex": "all",
   "rate_per_100k_py": 0.8,
   "ci_low": null,
   "ci_high": null,
   "country": "US (San Diego, CA)",
   "years": "1991-2000",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ADEM paragraph (ref 36)",
   "notes": "Secondary compilation; primary study named in location_in_source. Per 100,000 per year."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_100k_py": 1.37,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "per ref 60",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, narcolepsy paragraph; Table 2 (ref 60: Silber MH et al. Sleep 2002)",
   "notes": "Secondary compilation; primary study named in location_in_source. Chart-confirmed cases; per 100,000 population per year. Narcolepsy with cataplexy subset 0.74/100k."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "10-19",
   "sex": "all",
   "rate_per_100k_py": 3.84,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "per ref 60",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, narcolepsy paragraph (ref 60)",
   "notes": "Secondary compilation; primary study named in location_in_source. Peak decade."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "all ages",
   "sex": "male",
   "rate_per_100k_py": 1.72,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "per ref 60",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, narcolepsy paragraph (ref 60)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Narcolepsy",
   "age_band": "all ages",
   "sex": "female",
   "rate_per_100k_py": 1.05,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "per ref 60",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, narcolepsy paragraph (ref 60)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Pericarditis (acute, hospitalized)",
   "age_band": ">=16",
   "sex": "all",
   "rate_per_100k_py": 5.73,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Nationwide Inpatient Sample)",
   "years": "2003-2012",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, myocarditis/pericarditis paragraph 2; Table 2 (ref 62: Kumar N et al. Cardiology 2016)",
   "notes": "Secondary compilation; primary study named in location_in_source. Source gives 57.3 per million PY; /10. Hospitalizations only."
  },
  {
   "condition": "Pericarditis (acute, hospitalized)",
   "age_band": ">=65 (Medicare)",
   "sex": "all",
   "rate_per_100k_py": 26,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Medicare)",
   "years": "1999-2012",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, myocarditis/pericarditis paragraph 2; Table 2 (ref 63: Mody P et al.)",
   "notes": "Secondary compilation; primary study named in location_in_source. Hospitalization rate."
  },
  {
   "condition": "Venous thromboembolism",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_100k_py": 108,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Worcester, MA)",
   "years": "1985-2009",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Table 2, VTE row; Results VTE paragraph (ref 69: Huang W et al. Am J Med 2014)",
   "notes": "Secondary compilation; primary study named in location_in_source. Per 100,000 population per year."
  },
  {
   "condition": "Venous thromboembolism",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_100k_py": 117,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "25-year study (ref 70)",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, VTE paragraph (ref 70: Silverstein MD et al.)",
   "notes": "Secondary compilation; primary study named in location_in_source. Per 100,000 per year."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "35-44",
   "sex": "female",
   "rate_per_100k_py": 30,
   "ci_low": null,
   "ci_high": null,
   "country": "US (AHA Heart Disease & Stroke Statistics 2020)",
   "years": "per AHA 2020 update",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Table 2, MI row, lowest rate: US White females 35-44y, 0.3/1,000 PY (ref 73)",
   "notes": "Secondary compilation; primary study named in location_in_source. Source unit per 1,000 PY; x100. White females only."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": "75-84",
   "sex": "male",
   "rate_per_100k_py": 1590,
   "ci_low": null,
   "ci_high": null,
   "country": "US (AHA Heart Disease & Stroke Statistics 2020)",
   "years": "per AHA 2020 update",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Table 2, MI row, highest rate: US Black males 75-84y, 15.9/1,000 PY (ref 73)",
   "notes": "Secondary compilation; primary study named in location_in_source. Source unit per 1,000 PY; x100. Black males only."
  },
  {
   "condition": "Stroke (all types)",
   "age_band": ">=45",
   "sex": "all",
   "rate_per_100k_py": 410,
   "ci_low": null,
   "ci_high": null,
   "country": "US (ARIC cohort)",
   "years": "1987-2017",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, stroke paragraph 1 (refs 47-48: Koton S et al.)",
   "notes": "Secondary compilation; primary study named in location_in_source. Source 4.10 per 1,000 PY; x100."
  },
  {
   "condition": "Stroke (all types)",
   "age_band": ">=45",
   "sex": "male",
   "rate_per_100k_py": 459,
   "ci_low": null,
   "ci_high": null,
   "country": "US (ARIC cohort)",
   "years": "1987-2017",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, stroke paragraph 1 (refs 47-48)",
   "notes": "Secondary compilation; primary study named in location_in_source. Source 4.59 per 1,000 PY; x100."
  },
  {
   "condition": "Stroke (all types)",
   "age_band": ">=45",
   "sex": "female",
   "rate_per_100k_py": 374,
   "ci_low": null,
   "ci_high": null,
   "country": "US (ARIC cohort)",
   "years": "1987-2017",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, stroke paragraph 1 (refs 47-48)",
   "notes": "Secondary compilation; primary study named in location_in_source. Source 3.74 per 1,000 PY; x100."
  },
  {
   "condition": "Stroke (ischaemic and haemorrhagic)",
   "age_band": "<20",
   "sex": "all",
   "rate_per_100k_py": 4.6,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Northern California)",
   "years": "per ref 55",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, stroke paragraph 4; Table 2 (ref 55: Agrawal N et al. Stroke 2009)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Ischemic stroke",
   "age_band": "11 months-17 years",
   "sex": "all",
   "rate_per_100k_py": 1.2,
   "ci_low": null,
   "ci_high": null,
   "country": "US (VSD)",
   "years": "per ref 58",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, stroke paragraph 5 (ref 58: Donahue JG et al. Pediatrics 2009)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Kawasaki disease",
   "age_band": "<5 (hospitalization)",
   "sex": "all",
   "rate_per_100k_py": 19.8,
   "ci_low": null,
   "ci_high": null,
   "country": "US",
   "years": "2016",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, Kawasaki paragraph 1 (ref 90: CDC)",
   "notes": "Secondary compilation; primary study named in location_in_source. Hospitalizations per 100,000 children <5y. Paper also says continental US incidence is 9-20/100k in <5y."
  },
  {
   "condition": "Kawasaki disease",
   "age_band": "<5",
   "sex": "all",
   "rate_per_100k_py": 15.9,
   "ci_low": null,
   "ci_high": null,
   "country": "US (western New York)",
   "years": "16-year review (ref 91)",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, Kawasaki paragraph 1 (ref 91: Chang A et al.)",
   "notes": "Secondary compilation; primary study named in location_in_source. Table 2 of the same paper prints 15.8 for this study (internal discrepancy)."
  },
  {
   "condition": "Kawasaki disease",
   "age_band": "<5",
   "sex": "all",
   "rate_per_100k_py": 50.4,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Hawaii)",
   "years": "per ref 92",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, Kawasaki paragraph 1; Table 2 (ref 92: Holman RC et al.)",
   "notes": "Secondary compilation; primary study named in location_in_source. Highest US state rate."
  },
  {
   "condition": "Kawasaki disease",
   "age_band": "<18",
   "sex": "all",
   "rate_per_100k_py": 6.4,
   "ci_low": null,
   "ci_high": null,
   "country": "US",
   "years": "per ref 93",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, Kawasaki paragraph 2 (ref 93: Ghimire LV et al. 2019)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Kawasaki disease",
   "age_band": "<18 (hospitalization)",
   "sex": "all",
   "rate_per_100k_py": 7.5,
   "ci_low": null,
   "ci_high": null,
   "country": "US (KID + NIS)",
   "years": "per ref 94",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, Kawasaki paragraph 2 (ref 94: Holman RC et al.)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_100k_py": 42,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN; REP)",
   "years": "2001-2010",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, anaphylaxis paragraph 1; Table 2 (ref 102: Lee S et al. JACI 2017)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "all ages",
   "sex": "male",
   "rate_per_100k_py": 43.8,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN; REP)",
   "years": "2001-2010",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, anaphylaxis paragraph 1 (ref 102)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Anaphylaxis (all-cause)",
   "age_band": "all ages",
   "sex": "female",
   "rate_per_100k_py": 40.1,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN; REP)",
   "years": "2001-2010",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, anaphylaxis paragraph 1 (ref 102)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "all ages (claims)",
   "sex": "all",
   "rate_per_100k_py": 6.1,
   "ci_low": null,
   "ci_high": null,
   "country": "US (two private claims databases)",
   "years": "per ref 107",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ITP paragraph 1 (ref 107: Weycker D et al. J Med Econ 2020)",
   "notes": "Secondary compilation; primary study named in location_in_source. Per 100,000 per year."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "all ages (claims)",
   "sex": "female",
   "rate_per_100k_py": 6.7,
   "ci_low": null,
   "ci_high": null,
   "country": "US (claims)",
   "years": "per ref 107",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ITP paragraph 1 (ref 107)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "all ages (claims)",
   "sex": "male",
   "rate_per_100k_py": 5.5,
   "ci_low": null,
   "ci_high": null,
   "country": "US (claims)",
   "years": "per ref 107",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ITP paragraph 1 (ref 107)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "0-4",
   "sex": "all",
   "rate_per_100k_py": 8.1,
   "ci_low": null,
   "ci_high": null,
   "country": "US (claims)",
   "years": "per ref 107",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ITP paragraph 1 (ref 107)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": ">=65",
   "sex": "all",
   "rate_per_100k_py": 13.7,
   "ci_low": null,
   "ci_high": null,
   "country": "US (claims)",
   "years": "per ref 107",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ITP paragraph 1 (ref 107)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "<18",
   "sex": "all",
   "rate_per_100k_py": 8.8,
   "ci_low": null,
   "ci_high": null,
   "country": "US (commercial claims)",
   "years": "2011-2016 (Table 2)",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ITP paragraph 2; Table 2 (ref 108: Shaw J et al. Platelets 2020)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "<2",
   "sex": "all",
   "rate_per_100k_py": 14.8,
   "ci_low": null,
   "ci_high": null,
   "country": "US (commercial claims)",
   "years": "per ref 108",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ITP paragraph 2 (ref 108)",
   "notes": "Secondary compilation; primary study named in location_in_source."
  },
  {
   "condition": "Immune thrombocytopenia",
   "age_band": "<18",
   "sex": "all",
   "rate_per_100k_py": 2.7,
   "ci_low": null,
   "ci_high": null,
   "country": "US (VSD)",
   "years": "1991-2000 (Table 2)",
   "source": "Gubernot D et al. 2021 Vaccine (FDA/CDC literature review of US rates)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.05.016; PMC8118666",
   "location_in_source": "Results, ITP paragraph 2; Table 2 (ref 109: Glanz J et al. Pediatrics 2008)",
   "notes": "Secondary compilation; primary study named in location_in_source. Lower estimate."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "<=17",
   "sex": "all",
   "rate_per_100k_py": 0.81,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "Historical (Beghi 1985 study period)",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Guillain Barre, USA [27], age <=17",
   "notes": "Ref 27 = Beghi E et al. Arch Neurol 1985. Old data."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "18-39",
   "sex": "all",
   "rate_per_100k_py": 1.34,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "Historical (Beghi 1985 study period)",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Guillain Barre, USA [27], age 18-39",
   "notes": "Ref 27 = Beghi E et al. Arch Neurol 1985. Old data."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "40-59",
   "sex": "all",
   "rate_per_100k_py": 2.84,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "Historical (Beghi 1985 study period)",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Guillain Barre, USA [27], age 40-59",
   "notes": "Ref 27 = Beghi E et al. Arch Neurol 1985. Old data."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": ">=60",
   "sex": "all",
   "rate_per_100k_py": 3.25,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "Historical (Beghi 1985 study period)",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Guillain Barre, USA [27], age >=60",
   "notes": "Ref 27 = Beghi E et al. Arch Neurol 1985. Old data."
  },
  {
   "condition": "Guillain-Barre syndrome",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_100k_py": 1.68,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Olmsted County, MN)",
   "years": "Historical (Beghi 1985 study period)",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Guillain Barre, USA [27], age all ages",
   "notes": "Ref 27 = Beghi E et al. Arch Neurol 1985. Old data."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "0-9",
   "sex": "all",
   "rate_per_100k_py": 4.2,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Rochester, MN)",
   "years": "1968-1982",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Bell's Palsy, USA [22], age 0-9",
   "notes": "Ref 22 = Katusic SK et al. Ann Neurol 1986."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "10-19",
   "sex": "all",
   "rate_per_100k_py": 15.3,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Rochester, MN)",
   "years": "1968-1982",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Bell's Palsy, USA [22], age 10-19",
   "notes": "Ref 22 = Katusic SK et al. Ann Neurol 1986."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "20-29",
   "sex": "all",
   "rate_per_100k_py": 24.0,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Rochester, MN)",
   "years": "1968-1982",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Bell's Palsy, USA [22], age 20-29",
   "notes": "Ref 22 = Katusic SK et al. Ann Neurol 1986."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "30-39",
   "sex": "all",
   "rate_per_100k_py": 30.9,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Rochester, MN)",
   "years": "1968-1982",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Bell's Palsy, USA [22], age 30-39",
   "notes": "Ref 22 = Katusic SK et al. Ann Neurol 1986."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "40-49",
   "sex": "all",
   "rate_per_100k_py": 35.2,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Rochester, MN)",
   "years": "1968-1982",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Bell's Palsy, USA [22], age 40-49",
   "notes": "Ref 22 = Katusic SK et al. Ann Neurol 1986."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "50-59",
   "sex": "all",
   "rate_per_100k_py": 35.8,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Rochester, MN)",
   "years": "1968-1982",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Bell's Palsy, USA [22], age 50-59",
   "notes": "Ref 22 = Katusic SK et al. Ann Neurol 1986."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "60-69",
   "sex": "all",
   "rate_per_100k_py": 37.1,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Rochester, MN)",
   "years": "1968-1982",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Bell's Palsy, USA [22], age 60-69",
   "notes": "Ref 22 = Katusic SK et al. Ann Neurol 1986."
  },
  {
   "condition": "Bell's palsy",
   "age_band": ">=70",
   "sex": "all",
   "rate_per_100k_py": 52.7,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Rochester, MN)",
   "years": "1968-1982",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Bell's Palsy, USA [22], age >=70",
   "notes": "Ref 22 = Katusic SK et al. Ann Neurol 1986."
  },
  {
   "condition": "Bell's palsy",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_100k_py": 25.2,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Rochester, MN)",
   "years": "1968-1982",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Bell's Palsy, USA [22], age all ages",
   "notes": "Ref 22 = Katusic SK et al. Ann Neurol 1986."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "10-17",
   "sex": "male",
   "rate_per_100k_py": 0.7,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Northern California, Kaiser Permanente)",
   "years": "per ref 25",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Transverse Myelitis, N. California [25], age 10-17",
   "notes": "Ref 25 = Klein NP et al. Vaccine 2010."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "10-17",
   "sex": "female",
   "rate_per_100k_py": 0.4,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Northern California, Kaiser Permanente)",
   "years": "per ref 25",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Transverse Myelitis, N. California [25], age 10-17",
   "notes": "Ref 25 = Klein NP et al. Vaccine 2010."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "18-25",
   "sex": "male",
   "rate_per_100k_py": 0.4,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Northern California, Kaiser Permanente)",
   "years": "per ref 25",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Transverse Myelitis, N. California [25], age 18-25",
   "notes": "Ref 25 = Klein NP et al. Vaccine 2010."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "18-25",
   "sex": "female",
   "rate_per_100k_py": 1.1,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Northern California, Kaiser Permanente)",
   "years": "per ref 25",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Transverse Myelitis, N. California [25], age 18-25",
   "notes": "Ref 25 = Klein NP et al. Vaccine 2010."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "26-62",
   "sex": "male",
   "rate_per_100k_py": 2.4,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Northern California, Kaiser Permanente)",
   "years": "per ref 25",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Transverse Myelitis, N. California [25], age 26-62",
   "notes": "Ref 25 = Klein NP et al. Vaccine 2010."
  },
  {
   "condition": "Transverse myelitis",
   "age_band": "26-62",
   "sex": "female",
   "rate_per_100k_py": 4.9,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Northern California, Kaiser Permanente)",
   "years": "per ref 25",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Transverse Myelitis, N. California [25], age 26-62",
   "notes": "Ref 25 = Klein NP et al. Vaccine 2010."
  },
  {
   "condition": "Acute myocardial infarction",
   "age_band": ">30",
   "sex": "all",
   "rate_per_100k_py": 208,
   "ci_low": null,
   "ci_high": null,
   "country": "US (Kaiser Permanente Northern California)",
   "years": "2008",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Myocardial Infarction, USA [16], >30, 2008",
   "notes": "Ref 16 = Yeh RW et al. NEJM 2010. The 2000 rate in the same row was 287."
  },
  {
   "condition": "Kawasaki disease",
   "age_band": "all ages",
   "sex": "male",
   "rate_per_100k_py": 0.81,
   "ci_low": null,
   "ci_high": null,
   "country": "Europe (ADVANCE project databases)",
   "years": "per ref 29",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Kawasaki Disease, Europe [29]",
   "notes": "All-ages rate (diluted by adults). Ref 29 = Willame C et al. Drug Saf 2021."
  },
  {
   "condition": "Kawasaki disease",
   "age_band": "all ages",
   "sex": "female",
   "rate_per_100k_py": 0.52,
   "ci_low": null,
   "ci_high": null,
   "country": "Europe (ADVANCE project databases)",
   "years": "per ref 29",
   "source": "Black SB et al. 2021 Vaccine (The critical role of background rates of possible adverse events in the assessment of COVID-19 vaccine safety)",
   "doi_or_pmid": "10.1016/j.vaccine.2021.03.016; PMID 33846042; PMC7936550",
   "location_in_source": "Table 2, Kawasaki Disease, Europe [29]",
   "notes": "All-ages rate."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_100k_py": 2.85,
   "ci_low": 2.79,
   "ci_high": 2.91,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, all ages / all",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "0-17",
   "sex": "all",
   "rate_per_100k_py": 1.7,
   "ci_low": 1.61,
   "ci_high": 1.8,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 0-17 / all",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "18-29",
   "sex": "all",
   "rate_per_100k_py": 2.81,
   "ci_low": 2.67,
   "ci_high": 2.96,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 18-29 / all",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "30-39",
   "sex": "all",
   "rate_per_100k_py": 2.62,
   "ci_low": 2.47,
   "ci_high": 2.78,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 30-39 / all",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "40-49",
   "sex": "all",
   "rate_per_100k_py": 3.28,
   "ci_low": 3.11,
   "ci_high": 3.46,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 40-49 / all",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "50-64",
   "sex": "all",
   "rate_per_100k_py": 2.96,
   "ci_low": 2.82,
   "ci_high": 3.09,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 50-64 / all",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "65+",
   "sex": "all",
   "rate_per_100k_py": 4.23,
   "ci_low": 4.06,
   "ci_high": 4.41,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 65+ / all",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "all ages",
   "sex": "male",
   "rate_per_100k_py": 2.63,
   "ci_low": 2.55,
   "ci_high": 2.71,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, all ages / male",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "all ages",
   "sex": "female",
   "rate_per_100k_py": 3.07,
   "ci_low": 2.98,
   "ci_high": 3.15,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, all ages / female",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "0-17",
   "sex": "male",
   "rate_per_100k_py": 2.18,
   "ci_low": 2.03,
   "ci_high": 2.33,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 0-17 / male",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "0-17",
   "sex": "female",
   "rate_per_100k_py": 1.2,
   "ci_low": 1.09,
   "ci_high": 1.32,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 0-17 / female",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "18-29",
   "sex": "male",
   "rate_per_100k_py": 1.76,
   "ci_low": 1.61,
   "ci_high": 1.93,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 18-29 / male",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "18-29",
   "sex": "female",
   "rate_per_100k_py": 3.91,
   "ci_low": 3.67,
   "ci_high": 4.16,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 18-29 / female",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "30-39",
   "sex": "male",
   "rate_per_100k_py": 1.55,
   "ci_low": 1.39,
   "ci_high": 1.72,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 30-39 / male",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "30-39",
   "sex": "female",
   "rate_per_100k_py": 3.71,
   "ci_low": 3.46,
   "ci_high": 3.98,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 30-39 / female",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "40-49",
   "sex": "male",
   "rate_per_100k_py": 2.47,
   "ci_low": 2.26,
   "ci_high": 2.7,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 40-49 / male",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "40-49",
   "sex": "female",
   "rate_per_100k_py": 4.07,
   "ci_low": 3.8,
   "ci_high": 4.36,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 40-49 / female",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "50-64",
   "sex": "male",
   "rate_per_100k_py": 3.38,
   "ci_low": 3.18,
   "ci_high": 3.59,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 50-64 / male",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "50-64",
   "sex": "female",
   "rate_per_100k_py": 2.56,
   "ci_low": 2.39,
   "ci_high": 2.74,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 50-64 / female",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "65+",
   "sex": "male",
   "rate_per_100k_py": 4.53,
   "ci_low": 4.26,
   "ci_high": 4.81,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 65+ / male",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Cerebral venous sinus thrombosis",
   "age_band": "65+",
   "sex": "female",
   "rate_per_100k_py": 3.99,
   "ci_low": 3.76,
   "ci_high": 4.22,
   "country": "US (HCUP National Inpatient Sample)",
   "years": "2018",
   "source": "Payne AB et al. 2022 Res Pract Thromb Haemost (CDC)",
   "doi_or_pmid": "10.1002/rth2.12682; PMC8901465",
   "location_in_source": "Table 1, 2018 NIS column, 65+ / female",
   "notes": "CVST ICD-10-CM code anywhere on inpatient record; cases per 100,000 US population per year (approximates per 100k PY). CVST with thrombocytopenia about 0.21/100k (Table 2)."
  },
  {
   "condition": "Intussusception (hospitalized)",
   "age_band": "<1 year",
   "sex": "all",
   "rate_per_100k_py": 33.6,
   "ci_low": null,
   "ci_high": null,
   "country": "US (35 HCUP State Inpatient Databases, about 85% of birth cohort)",
   "years": "2002-2004 (pre-rotavirus-vaccine era)",
   "source": "Tate JE et al. 2008 Pediatrics",
   "doi_or_pmid": "10.1542/peds.2007-1590; PMC2680116",
   "location_in_source": "Table 1, row 'Total'",
   "notes": "Hospitalizations per 100,000 infants per year (approximates per 100k infant-years). ICD-9-CM 560.0. Peak about 62/100k at 26-29 weeks (Fig 4)."
  },
  {
   "condition": "Intussusception (hospitalized)",
   "age_band": "<1 year",
   "sex": "male",
   "rate_per_100k_py": 39.8,
   "ci_low": null,
   "ci_high": null,
   "country": "US (35 HCUP State Inpatient Databases, about 85% of birth cohort)",
   "years": "2002-2004 (pre-rotavirus-vaccine era)",
   "source": "Tate JE et al. 2008 Pediatrics",
   "doi_or_pmid": "10.1542/peds.2007-1590; PMC2680116",
   "location_in_source": "Table 1, row 'Male'",
   "notes": "Hospitalizations per 100,000 infants per year (approximates per 100k infant-years). ICD-9-CM 560.0. Peak about 62/100k at 26-29 weeks (Fig 4)."
  },
  {
   "condition": "Intussusception (hospitalized)",
   "age_band": "<1 year",
   "sex": "female",
   "rate_per_100k_py": 27.1,
   "ci_low": null,
   "ci_high": null,
   "country": "US (35 HCUP State Inpatient Databases, about 85% of birth cohort)",
   "years": "2002-2004 (pre-rotavirus-vaccine era)",
   "source": "Tate JE et al. 2008 Pediatrics",
   "doi_or_pmid": "10.1542/peds.2007-1590; PMC2680116",
   "location_in_source": "Table 1, row 'Female'",
   "notes": "Hospitalizations per 100,000 infants per year (approximates per 100k infant-years). ICD-9-CM 560.0. Peak about 62/100k at 26-29 weeks (Fig 4)."
  },
  {
   "condition": "Intussusception (hospitalized)",
   "age_band": "1-5 weeks",
   "sex": "all",
   "rate_per_100k_py": 4.3,
   "ci_low": null,
   "ci_high": null,
   "country": "US (35 HCUP State Inpatient Databases, about 85% of birth cohort)",
   "years": "2002-2004 (pre-rotavirus-vaccine era)",
   "source": "Tate JE et al. 2008 Pediatrics",
   "doi_or_pmid": "10.1542/peds.2007-1590; PMC2680116",
   "location_in_source": "Table 1, row 'Age 1-5 wk'",
   "notes": "Hospitalizations per 100,000 infants per year (approximates per 100k infant-years). ICD-9-CM 560.0. Peak about 62/100k at 26-29 weeks (Fig 4)."
  },
  {
   "condition": "Intussusception (hospitalized)",
   "age_band": "6-14 weeks",
   "sex": "all",
   "rate_per_100k_py": 11.6,
   "ci_low": null,
   "ci_high": null,
   "country": "US (35 HCUP State Inpatient Databases, about 85% of birth cohort)",
   "years": "2002-2004 (pre-rotavirus-vaccine era)",
   "source": "Tate JE et al. 2008 Pediatrics",
   "doi_or_pmid": "10.1542/peds.2007-1590; PMC2680116",
   "location_in_source": "Table 1, row 'Age 6-14 wk'",
   "notes": "Hospitalizations per 100,000 infants per year (approximates per 100k infant-years). ICD-9-CM 560.0. Peak about 62/100k at 26-29 weeks (Fig 4)."
  },
  {
   "condition": "Intussusception (hospitalized)",
   "age_band": "15-24 weeks",
   "sex": "all",
   "rate_per_100k_py": 40.1,
   "ci_low": null,
   "ci_high": null,
   "country": "US (35 HCUP State Inpatient Databases, about 85% of birth cohort)",
   "years": "2002-2004 (pre-rotavirus-vaccine era)",
   "source": "Tate JE et al. 2008 Pediatrics",
   "doi_or_pmid": "10.1542/peds.2007-1590; PMC2680116",
   "location_in_source": "Table 1, row 'Age 15-24 wk'",
   "notes": "Hospitalizations per 100,000 infants per year (approximates per 100k infant-years). ICD-9-CM 560.0. Peak about 62/100k at 26-29 weeks (Fig 4)."
  },
  {
   "condition": "Intussusception (hospitalized)",
   "age_band": "25-32 weeks",
   "sex": "all",
   "rate_per_100k_py": 54.3,
   "ci_low": null,
   "ci_high": null,
   "country": "US (35 HCUP State Inpatient Databases, about 85% of birth cohort)",
   "years": "2002-2004 (pre-rotavirus-vaccine era)",
   "source": "Tate JE et al. 2008 Pediatrics",
   "doi_or_pmid": "10.1542/peds.2007-1590; PMC2680116",
   "location_in_source": "Table 1, row 'Age 25-32 wk'",
   "notes": "Hospitalizations per 100,000 infants per year (approximates per 100k infant-years). ICD-9-CM 560.0. Peak about 62/100k at 26-29 weeks (Fig 4)."
  },
  {
   "condition": "Intussusception (hospitalized)",
   "age_band": "33-52 weeks",
   "sex": "all",
   "rate_per_100k_py": 39.3,
   "ci_low": null,
   "ci_high": null,
   "country": "US (35 HCUP State Inpatient Databases, about 85% of birth cohort)",
   "years": "2002-2004 (pre-rotavirus-vaccine era)",
   "source": "Tate JE et al. 2008 Pediatrics",
   "doi_or_pmid": "10.1542/peds.2007-1590; PMC2680116",
   "location_in_source": "Table 1, row 'Age 33-52 wk'",
   "notes": "Hospitalizations per 100,000 infants per year (approximates per 100k infant-years). ICD-9-CM 560.0. Peak about 62/100k at 26-29 weeks (Fig 4)."
  },
  {
   "condition": "Febrile seizure (first)",
   "age_band": "3-60 months",
   "sex": "female",
   "rate_per_100k_py": 706.8,
   "ci_low": 699.6,
   "ci_high": 714.0,
   "country": "Denmark (national registers)",
   "years": "Children born 1977-2011, followed to 2016",
   "source": "Christensen KJ et al. 2021 Acta Neurol Scand",
   "doi_or_pmid": "10.1111/ane.13420; PMC8178233",
   "location_in_source": "Results, paragraph 1",
   "notes": "Source gives 58.9 (95% CI 58.3-59.5) per 100,000 person-MONTHS; multiplied by 12 for person-years (unit conversion only). Hospital/outpatient ICD diagnoses. 5-year cumulative incidence 3.59%. Age band is 3-60 months, not 6-60."
  },
  {
   "condition": "Febrile seizure (first)",
   "age_band": "3-60 months",
   "sex": "male",
   "rate_per_100k_py": 853.2,
   "ci_low": 846.0,
   "ci_high": 861.6,
   "country": "Denmark (national registers)",
   "years": "Children born 1977-2011, followed to 2016",
   "source": "Christensen KJ et al. 2021 Acta Neurol Scand",
   "doi_or_pmid": "10.1111/ane.13420; PMC8178233",
   "location_in_source": "Results, paragraph 1",
   "notes": "Source gives 71.1 (95% CI 70.5-71.8) per 100,000 person-MONTHS; multiplied by 12 for person-years (unit conversion only). Hospital/outpatient ICD diagnoses. 5-year cumulative incidence 3.59%. Age band is 3-60 months, not 6-60."
  },
  {
   "condition": "Herpes zoster",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_100k_py": 447,
   "ci_low": 444,
   "ci_high": 450,
   "country": "US (MarketScan commercial + Medicare supplemental; immunocompetent, unvaccinated)",
   "years": "2011",
   "source": "Johnson BH et al. 2015 BMC Infect Dis",
   "doi_or_pmid": "10.1186/s12879-015-1262-8; PMC4636742",
   "location_in_source": "Abstract results and Results section",
   "notes": "Source unit per 1,000 PY (e.g. 4.47); x100. Zoster-vaccinated persons excluded. Age/sex-standardised rate 4.63/1,000 PY."
  },
  {
   "condition": "Herpes zoster",
   "age_band": "<=19",
   "sex": "all",
   "rate_per_100k_py": 86,
   "ci_low": 84,
   "ci_high": 88,
   "country": "US (MarketScan commercial + Medicare supplemental; immunocompetent, unvaccinated)",
   "years": "2011",
   "source": "Johnson BH et al. 2015 BMC Infect Dis",
   "doi_or_pmid": "10.1186/s12879-015-1262-8; PMC4636742",
   "location_in_source": "Abstract results and Results section",
   "notes": "Source unit per 1,000 PY (e.g. 4.47); x100. Zoster-vaccinated persons excluded. Age/sex-standardised rate 4.63/1,000 PY."
  },
  {
   "condition": "Herpes zoster",
   "age_band": ">=80",
   "sex": "all",
   "rate_per_100k_py": 1278,
   "ci_low": 1249,
   "ci_high": 1307,
   "country": "US (MarketScan commercial + Medicare supplemental; immunocompetent, unvaccinated)",
   "years": "2011",
   "source": "Johnson BH et al. 2015 BMC Infect Dis",
   "doi_or_pmid": "10.1186/s12879-015-1262-8; PMC4636742",
   "location_in_source": "Abstract results and Results section",
   "notes": "Source unit per 1,000 PY (e.g. 4.47); x100. Zoster-vaccinated persons excluded. Age/sex-standardised rate 4.63/1,000 PY."
  },
  {
   "condition": "Herpes zoster",
   "age_band": ">=50",
   "sex": "all",
   "rate_per_100k_py": 846,
   "ci_low": 839,
   "ci_high": 852,
   "country": "US (MarketScan commercial + Medicare supplemental; immunocompetent, unvaccinated)",
   "years": "2011",
   "source": "Johnson BH et al. 2015 BMC Infect Dis",
   "doi_or_pmid": "10.1186/s12879-015-1262-8; PMC4636742",
   "location_in_source": "Abstract results and Results section",
   "notes": "Source unit per 1,000 PY (e.g. 4.47); x100. Zoster-vaccinated persons excluded. Age/sex-standardised rate 4.63/1,000 PY."
  },
  {
   "condition": "Herpes zoster",
   "age_band": ">=60",
   "sex": "all",
   "rate_per_100k_py": 1046,
   "ci_low": 1035,
   "ci_high": 1056,
   "country": "US (MarketScan commercial + Medicare supplemental; immunocompetent, unvaccinated)",
   "years": "2011",
   "source": "Johnson BH et al. 2015 BMC Infect Dis",
   "doi_or_pmid": "10.1186/s12879-015-1262-8; PMC4636742",
   "location_in_source": "Abstract results and Results section",
   "notes": "Source unit per 1,000 PY (e.g. 4.47); x100. Zoster-vaccinated persons excluded. Age/sex-standardised rate 4.63/1,000 PY."
  },
  {
   "condition": "Herpes zoster",
   "age_band": "all ages",
   "sex": "female",
   "rate_per_100k_py": 525,
   "ci_low": 521,
   "ci_high": 529,
   "country": "US (MarketScan commercial + Medicare supplemental; immunocompetent, unvaccinated)",
   "years": "2011",
   "source": "Johnson BH et al. 2015 BMC Infect Dis",
   "doi_or_pmid": "10.1186/s12879-015-1262-8; PMC4636742",
   "location_in_source": "Abstract results and Results section",
   "notes": "Source unit per 1,000 PY (e.g. 4.47); x100. Zoster-vaccinated persons excluded. Age/sex-standardised rate 4.63/1,000 PY."
  },
  {
   "condition": "Herpes zoster",
   "age_band": "all ages",
   "sex": "male",
   "rate_per_100k_py": 366,
   "ci_low": 362,
   "ci_high": 369,
   "country": "US (MarketScan commercial + Medicare supplemental; immunocompetent, unvaccinated)",
   "years": "2011",
   "source": "Johnson BH et al. 2015 BMC Infect Dis",
   "doi_or_pmid": "10.1186/s12879-015-1262-8; PMC4636742",
   "location_in_source": "Abstract results and Results section",
   "notes": "Source unit per 1,000 PY (e.g. 4.47); x100. Zoster-vaccinated persons excluded. Age/sex-standardised rate 4.63/1,000 PY."
  },
  {
   "condition": "Anaphylaxis after vaccination (vaccine-triggered)",
   "age_band": "all ages",
   "sex": "all",
   "rate_per_million_doses": 1.31,
   "ci_low": 0.9,
   "ci_high": 1.84,
   "country": "US (Vaccine Safety Datalink)",
   "years": "2009-2011",
   "source": "McNeil MM et al. 2016 J Allergy Clin Immunol (Vaccine Safety Datalink)",
   "doi_or_pmid": "10.1016/j.jaci.2015.07.048; PMID 26452420; PMC4783279",
   "location_in_source": "Table VII, Results text / all vaccines",
   "notes": "Rate per MILLION vaccine doses (33 cases / 25,173,965 doses); chart-confirmed Brighton level 1-2; 0-2 day window. Per vaccination visit: 1.87 (1.29-2.63) per million."
  },
  {
   "condition": "Anaphylaxis after vaccination (vaccine-triggered)",
   "age_band": "0-17",
   "sex": "all",
   "rate_per_million_doses": 1.45,
   "ci_low": 0.86,
   "ci_high": 2.29,
   "country": "US (Vaccine Safety Datalink)",
   "years": "2009-2011",
   "source": "McNeil MM et al. 2016 J Allergy Clin Immunol (Vaccine Safety Datalink)",
   "doi_or_pmid": "10.1016/j.jaci.2015.07.048; PMID 26452420; PMC4783279",
   "location_in_source": "Table VII, Age group 0-17",
   "notes": "Rate per MILLION vaccine doses (33 cases / 25,173,965 doses); chart-confirmed Brighton level 1-2; 0-2 day window. Per vaccination visit: 1.87 (1.29-2.63) per million."
  },
  {
   "condition": "Anaphylaxis after vaccination (vaccine-triggered)",
   "age_band": "18-49",
   "sex": "all",
   "rate_per_million_doses": 1.78,
   "ci_low": 0.81,
   "ci_high": 3.37,
   "country": "US (Vaccine Safety Datalink)",
   "years": "2009-2011",
   "source": "McNeil MM et al. 2016 J Allergy Clin Immunol (Vaccine Safety Datalink)",
   "doi_or_pmid": "10.1016/j.jaci.2015.07.048; PMID 26452420; PMC4783279",
   "location_in_source": "Table VII, Age group 18-49",
   "notes": "Rate per MILLION vaccine doses (33 cases / 25,173,965 doses); chart-confirmed Brighton level 1-2; 0-2 day window. Per vaccination visit: 1.87 (1.29-2.63) per million."
  },
  {
   "condition": "Anaphylaxis after vaccination (vaccine-triggered)",
   "age_band": ">=50",
   "sex": "all",
   "rate_per_million_doses": 0.78,
   "ci_low": 0.29,
   "ci_high": 1.69,
   "country": "US (Vaccine Safety Datalink)",
   "years": "2009-2011",
   "source": "McNeil MM et al. 2016 J Allergy Clin Immunol (Vaccine Safety Datalink)",
   "doi_or_pmid": "10.1016/j.jaci.2015.07.048; PMID 26452420; PMC4783279",
   "location_in_source": "Table VII, Age group >=50",
   "notes": "Rate per MILLION vaccine doses (33 cases / 25,173,965 doses); chart-confirmed Brighton level 1-2; 0-2 day window. Per vaccination visit: 1.87 (1.29-2.63) per million."
  },
  {
   "condition": "Anaphylaxis after vaccination (vaccine-triggered)",
   "age_band": "all ages",
   "sex": "female",
   "rate_per_million_doses": 1.45,
   "ci_low": 0.89,
   "ci_high": 2.24,
   "country": "US (Vaccine Safety Datalink)",
   "years": "2009-2011",
   "source": "McNeil MM et al. 2016 J Allergy Clin Immunol (Vaccine Safety Datalink)",
   "doi_or_pmid": "10.1016/j.jaci.2015.07.048; PMID 26452420; PMC4783279",
   "location_in_source": "Table VII, Sex Female",
   "notes": "Rate per MILLION vaccine doses (33 cases / 25,173,965 doses); chart-confirmed Brighton level 1-2; 0-2 day window. Per vaccination visit: 1.87 (1.29-2.63) per million."
  },
  {
   "condition": "Anaphylaxis after vaccination (vaccine-triggered)",
   "age_band": "all ages",
   "sex": "male",
   "rate_per_million_doses": 1.14,
   "ci_low": 0.61,
   "ci_high": 1.95,
   "country": "US (Vaccine Safety Datalink)",
   "years": "2009-2011",
   "source": "McNeil MM et al. 2016 J Allergy Clin Immunol (Vaccine Safety Datalink)",
   "doi_or_pmid": "10.1016/j.jaci.2015.07.048; PMID 26452420; PMC4783279",
   "location_in_source": "Table VII, Sex Male",
   "notes": "Rate per MILLION vaccine doses (33 cases / 25,173,965 doses); chart-confirmed Brighton level 1-2; 0-2 day window. Per vaccination visit: 1.87 (1.29-2.63) per million."
  },
  {
   "condition": "Sudden infant death syndrome (SIDS, ICD-10 R95)",
   "age_band": "<1 year",
   "sex": "all",
   "rate_per_100k_live_births": 33.4,
   "ci_low": null,
   "ci_high": null,
   "country": "US (national, linked birth/infant death file)",
   "years": "2019",
   "source": "Ely DM, Driscoll AK. 2021 National Vital Statistics Reports 70(14): Infant Mortality in the United States, 2019",
   "doi_or_pmid": "NVSR vol 70 no 14 (CDC/NCHS) https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-14.pdf",
   "location_in_source": "Table 3, SIDS (R95) column, year 2019",
   "notes": "Rate per 100,000 LIVE BIRTHS (not person-years). SIDS only: excludes unknown cause (R99) and accidental suffocation/strangulation in bed (W75), so total SUID is higher (SUID rate not verified). 2019 count 1,251."
  },
  {
   "condition": "Sudden infant death syndrome (SIDS, ICD-10 R95)",
   "age_band": "<1 year",
   "sex": "all",
   "rate_per_100k_live_births": 35.1,
   "ci_low": null,
   "ci_high": null,
   "country": "US (national, linked birth/infant death file)",
   "years": "2018",
   "source": "Ely DM, Driscoll AK. 2021 National Vital Statistics Reports 70(14): Infant Mortality in the United States, 2019",
   "doi_or_pmid": "NVSR vol 70 no 14 (CDC/NCHS) https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-14.pdf",
   "location_in_source": "Table 3, SIDS (R95) column, year 2018",
   "notes": "Rate per 100,000 LIVE BIRTHS (not person-years). SIDS only: excludes unknown cause (R99) and accidental suffocation/strangulation in bed (W75), so total SUID is higher (SUID rate not verified). 2019 count 1,251."
  },
  {
   "condition": "Sudden infant death syndrome (SIDS, ICD-10 R95)",
   "age_band": "<1 year",
   "sex": "all",
   "rate_per_100k_live_births": 35.3,
   "ci_low": null,
   "ci_high": null,
   "country": "US (national, linked birth/infant death file)",
   "years": "2017",
   "source": "Ely DM, Driscoll AK. 2021 National Vital Statistics Reports 70(14): Infant Mortality in the United States, 2019",
   "doi_or_pmid": "NVSR vol 70 no 14 (CDC/NCHS) https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-14.pdf",
   "location_in_source": "Table 3, SIDS (R95) column, year 2017",
   "notes": "Rate per 100,000 LIVE BIRTHS (not person-years). SIDS only: excludes unknown cause (R99) and accidental suffocation/strangulation in bed (W75), so total SUID is higher (SUID rate not verified). 2019 count 1,251."
  },
  {
   "condition": "Sudden infant death syndrome (SIDS, ICD-10 R95)",
   "age_band": "<1 year",
   "sex": "all",
   "rate_per_100k_live_births": 38.0,
   "ci_low": null,
   "ci_high": null,
   "country": "US (national, linked birth/infant death file)",
   "years": "2016",
   "source": "Ely DM, Driscoll AK. 2021 National Vital Statistics Reports 70(14): Infant Mortality in the United States, 2019",
   "doi_or_pmid": "NVSR vol 70 no 14 (CDC/NCHS) https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-14.pdf",
   "location_in_source": "Table 3, SIDS (R95) column, year 2016",
   "notes": "Rate per 100,000 LIVE BIRTHS (not person-years). SIDS only: excludes unknown cause (R99) and accidental suffocation/strangulation in bed (W75), so total SUID is higher (SUID rate not verified). 2019 count 1,251."
  },
  {
   "condition": "Sudden infant death syndrome (SIDS, ICD-10 R95)",
   "age_band": "<1 year",
   "sex": "all",
   "rate_per_100k_live_births": 39.4,
   "ci_low": null,
   "ci_high": null,
   "country": "US (national, linked birth/infant death file)",
   "years": "2015",
   "source": "Ely DM, Driscoll AK. 2021 National Vital Statistics Reports 70(14): Infant Mortality in the United States, 2019",
   "doi_or_pmid": "NVSR vol 70 no 14 (CDC/NCHS) https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-14.pdf",
   "location_in_source": "Table 3, SIDS (R95) column, year 2015",
   "notes": "Rate per 100,000 LIVE BIRTHS (not person-years). SIDS only: excludes unknown cause (R99) and accidental suffocation/strangulation in bed (W75), so total SUID is higher (SUID rate not verified). 2019 count 1,251."
  }
 ],
 "not_found": [
  "Abara WE et al. J Infect Dis 2022 (PMC8755334, meta-analytic expected rates): only the abstract was retrievable (PDF behind a browser check); no values recorded.",
  "Febrile seizures: no US per-person-time rate for 6-60 months verified; only the Danish register rate (3-60 months) is recorded.",
  "SUID (SIDS + unknown cause + ASSB) rate per 100,000 live births: the CDC SUID data page now gives only 2024 counts; no rate verified.",
  "Kawasaki disease: no primary US age-specific person-time rate opened; only Gubernot-cited values recorded.",
  "Myocarditis alone in the US general population: not verified (Gubernot gives only a military rate; Willame gives Europe 3.18/100k PY).",
  "Black 2021 Table 2 anaphylaxis rows (USA National 0-18, 2006/2008) omitted: the table layout is ambiguous about whether 24.9 is a pediatric or an all-ages rate.",
  "Li 2021 Figure 3 cells printed only as '<1' (AMI female 1-5 and 6-17, AMI male 1-5) omitted because no numeric value is given.",
  "Appendicitis: no US-only rate verified; only the Li 2021 multinational pooled rates are recorded."
 ]
}