Adverse events of special interest for COVID-19 vaccines - background incidences vary by sex, age and time period and are affected by the pandemic

  1. Fredrik Nyberg
  2. Magnus Lindh
  3. Lowie E.G.W. Vanfleteren
  4. Niklas Hammar
  5. Björn Wettermark
  6. Johan Sundström
  7. Ailiana Santosa
  8. Brian K. Kirui
  9. Magnus Gisslén

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Abstract

Background

With large-scale COVID-19 vaccination implemented world-wide, safety signals needing rapid evaluation will emerge. We report population-based, age- and-sex-specific background incidence rates of conditions representing potential vaccine adverse events of special interest (AESI) for the Swedish general population using register data.

Methods

We studied an age/sex-stratified random 10% sample of the Swedish population on 1 Jan 2020, followed for AESI outcomes during 1 year, as the COVID-19 pandemic emerged and developed, before the start of vaccinations. We selected and defined the following outcomes based on information from regulatory authorities, large-scale adverse events initiatives and previous studies: aseptic meningitis, febrile seizure, Kawasaki syndrome, MISC, post-infectious arthritis, arthritis, myocarditis, ARDS, myocardial infarction, stroke, ischemic stroke, hemorrhagic stroke, venous thromboembolism, pulmonary embolism, kidney failure, liver failure, erythema multiforme, disseminated intravascular coagulation, autoimmune thyroiditis, and appendicitis. We calculated incidence rates stratified by age, sex and time period (quarters of 2020), and classified them using Council of International Organizations of Medical Sciences (CIOMS) categories: very common, common, uncommon, rare, or very rare.

Results

We included 972,723 study subjects, representing the Swedish national population on 1 Jan 2020. We found that AESI incidence rates vary greatly by age and in some cases sex. Several common AESIs showed expected increase with age, while some (e.g. appendicitis, aseptic meningitis, autoimmune thyroiditis, Kawasaki syndrome and MISC) were more common in young people, and others exhibited a flatter age pattern (e.g. myocarditis, DIC and erythema multiforme). Consequently, the CIOMS classification for AESIs varied widely according to age. Considerable variability was suggested for some AESI rates across the 4 quarters of 2020, potentially related to pandemic waves, seasonal variation, healthcare system overload or other healthcare delivery effects.

Conclusion

Age, sex, and timing of rates are important to consider when background AESI rates are compared to corresponding rates observed with COVID-19 vaccines.

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  1. ScreenIT

    SciScore for 10.1101/2021.10.04.21263507: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses were performed using the R statistical program version 4.0.2 (13).
    R statistical program
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    A limitation of this observational study in common with most, is that all outcomes may be subject to measurement error. As all outcome definitions are based on the presence of specific ICD-10 codes and were not further validated, they may lack in sensitivity or specificity, which may affect the estimated incidence rates. However, as a reflection of actual healthcare encounters in the Swedish healthcare system, many of these codes and algorithms have been shown to have good validity (10, 24). Interestingly, the existence of different patterns of misclassification in different datasets is in fact a strong argument to use the same data source, population and time period for both groups compared when conducting AESI evaluation. The analysis relied on data from 2020 using a target population that was a defined random sample of the total Swedish population on 1 Jan 2020. This provides our analysis with a good level of generalizability. We did not exclude individuals with previous events of the same kind as the AESIs. This design choice is aligned with real-life concerns where AESIs will be an issue whether they occur in people with or without underlying or pre-existing conditions. For many conditions, rates of events are generally somewhat higher in individuals with underlying comorbidity of the same type, but in most cases this difference is not very large and the group with underlying comorbidity is a small minority of the total population, so that rates estimated after excluding...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.10.04.21263507v1 on medRxiv