Background incidence rates of selected adverse events of special interest (AESI) to monitor the safety of COVID-19 vaccines

为监测 COVID-19 疫苗的安全性,选取特定不良事件(AESI)的背景发生率

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Abstract

BACKGROUND: Determining background rates of medical conditions identified as adverse events of special interest (AESI) that may occur following COVID-19 vaccination is important for contextualising and investigating potential vaccine safety signals. METHODS: We conducted a retrospective population-based cohort study using linked emergency department, hospitalisation and death data for 2017 and 2018 from Australia's most populous state, New South Wales. Incident cases of select neurological conditions, arterial or venous thromboembolic conditions, secondary thrombocytopenia, myocarditis/pericarditis, and unique events of anaphylaxis and generalised convulsions were identified using internationally agreed upon diagnostic (ICD-10) codes. State-specific rates per 100,000 person-years were calculated, with further stratification by age group and sex where clinically relevant to the condition, and the number of expected cases nationally in one and 6 weeks was estimated. RESULTS: Background rates of selected neurological conditions were low with the exception of generalised convulsions for which 1,599-1,872 cases were estimated nationally in a 1-week period in the absence of vaccination. Using a narrow case definition, rates of Guillain-Barré Syndrome (3.9 per 100,000 person-years) were higher than international rates reported elsewhere. Thromboembolic and cerebral venous sinus thrombosis event rates increased with age. Myocarditis occurred more commonly in males, and was highest in males aged 18-24 years, with an estimated 1-4 cases expected nationally in a 1-week period. CONCLUSIONS: Using routinely collected linked healthcare data provides localised estimates of background rates of new onset or periodic AESI which enables rapid estimation of observed-versus-expected rates of events reported following COVID-19 vaccination. This Australian-specific analysis contributes AESI background rates which can be compared with those from other countries to enhance understanding of geographic variability in the frequency of specific AESI in the absence of vaccination, and can be utilised for signal detection during program implementation.

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