{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T06:45:14Z","timestamp":1783579514239,"version":"3.55.0"},"reference-count":43,"publisher":"BMJ","license":[{"start":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T00:00:00Z","timestamp":1623628800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To quantify the background incidence rates of 15 prespecified adverse events\n                        of special interest (AESIs) associated with covid-19 vaccines.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Multinational network cohort study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting<\/jats:title>\n                    <jats:p>Electronic health records and health claims data from eight countries:\n                        Australia, France, Germany, Japan, the Netherlands, Spain, the United\n                        Kingdom, and the United States, mapped to a common data model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants<\/jats:title>\n                    <jats:p>126\u2009661\u2009070 people observed for at least 365 days before 1 January 2017,\n                        2018, or 2019 from 13 databases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Main outcome measures<\/jats:title>\n                    <jats:p>Events of interests were 15 prespecified AESIs (non-haemorrhagic and\n                        haemorrhagic stroke, acute myocardial infarction, deep vein thrombosis,\n                        pulmonary embolism, anaphylaxis, Bell\u2019s palsy, myocarditis or pericarditis,\n                        narcolepsy, appendicitis, immune thrombocytopenia, disseminated\n                        intravascular coagulation, encephalomyelitis (including acute disseminated\n                        encephalomyelitis), Guillain-Barr\u00e9 syndrome, and transverse myelitis).\n                        Incidence rates of AESIs were stratified by age, sex, and database. Rates\n                        were pooled across databases using random effects meta-analyses and\n                        classified according to the frequency categories of the Council for\n                        International Organizations of Medical Sciences.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Background rates varied greatly between databases. Deep vein thrombosis\n                        ranged from 387 (95% confidence interval 370 to 404) per 100\u2009000 person\n                        years in UK CPRD GOLD data to 1443 (1416 to 1470) per 100\u2009000 person years\n                        in US IBM MarketScan Multi-State Medicaid data among women aged 65 to 74\n                        years. Some AESIs increased with age. For example, myocardial infarction\n                        rates in men increased from 28 (27 to 29) per 100\u2009000 person years among\n                        those aged 18-34 years to 1400 (1374 to 1427) per 100\u2009000 person years in\n                        those older than 85 years in US Optum electronic health record data. Other\n                        AESIs were more common in young people. For example, rates of anaphylaxis\n                        among boys and men were 78 (75 to 80) per 100\u2009000 person years in those aged\n                        6-17 years and 8 (6 to 10) per 100\u2009000 person years in those older than 85\n                        years in Optum electronic health record data. Meta-analytic estimates of\n                        AESI rates were classified according to age and sex.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study found large variations in the observed rates of AESIs by age group\n                        and sex, showing the need for stratification or standardisation before using\n                        background rates for safety surveillance. Considerable population level\n                        heterogeneity in AESI rates was found between databases.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmj.n1435","type":"journal-article","created":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T08:30:11Z","timestamp":1623659411000},"page":"n1435","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":122,"title":["Characterising the background incidence rates of adverse events of special interest for covid-19 vaccines in eight countries: multinational network cohort study"],"prefix":"10.1136","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6872-5804","authenticated-orcid":false,"given":"Xintong","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Ostropolets","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rupa","family":"Makadia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Azza","family":"Shoaibi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gowtham","family":"Rao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8630-5347","authenticated-orcid":false,"given":"Anthony G","family":"Sena","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8317-7068","authenticated-orcid":false,"given":"Eugenia","family":"Martinez-Hernandez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonella","family":"Delmestri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katia","family":"Verhamme","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter R","family":"Rijnbeek","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Talita","family":"Duarte-Salles","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marc A","family":"Suchard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick B","family":"Ryan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George","family":"Hripcsak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3950-6346","authenticated-orcid":false,"given":"Daniel","family":"Prieto-Alhambra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2021,6,14]]},"reference":[{"key":"2021062407550534000_373.jun11_3.n1435.1","unstructured":"WHO COVID-19 Dashboard. 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