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  1. Version 2 published on medRxiv
  2. NCRC

    Our take

    There is growing evidence that myocarditis, or inflammation of the heart muscle, is an infrequent adverse event occurring predominantly in adolescent boys who have received the second dose of the Pfizer-BioNTech vaccine. A recent CDC study on this topic estimated the harms and benefits associated with vaccination and concluded that the benefits exceed the harms across all age groups for both boys and girls. Similarly, other studies have estimated vaccine-associated myocarditis risks using an active surveillance system called the Vaccine Safety Datalink. This study used data from the US Vaccine Adverse Events Reporting System (VAERS) to conduct a similar analysis, and found higher rates of myocarditis than in previous studies. However, VAERS is an open, passive surveillance system that is not suitable for this kind of analysis and is prone to overestimating vaccine side effects because cases are not subject to clinical adjudication. The authors went on to compare these estimated myocarditis risks with pediatric COVID-19 hospitalization rates, which is highly misleading. Preliminary data suggest that the clinical course of vaccine-associated myocarditis is favorable, while COVID-19 hospitalization is more likely to result in ICU admission, and rarely, death. Any implication that vaccination is more dangerous to boys than COVID-19 is entirely unsupported by this study.

    Study design

    other

    Study population and setting

    This study used data from the US Vaccine Adverse Events Reporting System (VAERS), a passive surveillance system not subject to clinical adjudication, from January to June 2021 to estimate rates of reported myocarditis and related symptoms among children aged 12-17 years who received mRNA vaccination against SARS-CoV-2 infection. The authors defined a “cardiac adverse event” (CAE) by the presence of one of the following in the symptom notes: myocarditis, pericarditis, myopericarditis, acute myocardial infarction, elevated troponin, abnormal EKG, abnormal echocardiogram, or cardiac MRI results consistent with myocarditis. Rates of CAE were calculated by age group (12-15 years and 16-17 years) and sex, and by vaccine dose (first or second). The authors then attempted a harm-benefit analysis by comparing their estimates of vaccine-associated CAEs with 120-day pediatric COVID-19 hospitalization rates, stratified by presence/absence of comorbidities. Hospitalization rates were derived from COVID-NET during three periods: January 2021 (high incidence), June 2021 (low incidence), and August 2021 (medium incidence).

    Summary of main findings

    There were 257 cardiac adverse events (90% among males) reported in the VAERS during the study period that met the authors’ search criteria. Among these reports, all children but one (Moderna) had received the Pfizer-BioNTech vaccine, as it was the only one approved for use in children younger than 18 years during the study period. The majority (85%) of CAE reports occurred after the second dose. The estimated incidence of CAEs among boys aged 12-15 years following the second dose was 162 per million; the incidence among boys aged 16-17 years was 94 per million. The estimated incidence of CAEs among girls was 13 per million in both age groups. The incidence of CAEs was considerably lower after the first dose across all age and sex groups. Median peak troponin was 5.2 ng/mL among boys aged 12-15 years, 11.6 ng/mL among boys aged 16-17 years, 0.8 ng/mL among girls aged 12-15 years, and 7.3 ng/mL among girls aged 16-17 years. The authors compared these estimates of CAE incidence against 120-day COVID-19 hospitalization, concluding that for boys without comorbidities, a vaccine-associated CAE was several times more likely than a COVID-19 hospitalization (the ratios varied by sex, age, and whether hospitalization rates were calculated during times of low or high incidence).

    Study strengths

    The authors made their data publicly available and easily accessible.

    Limitations

    A primary problem with this study is its reliance on VAERS data for estimating incidence of myocarditis without any clinical adjudication, secondary data, or control data. The VAERS is an open, passive surveillance system in which any member of the public can submit a report; it is an early-warning system designed to flag symptoms and issues worthy of more rigorous study, and is not designed to be used for the purposes attempted here. The criteria for defining a cardiac adverse event were overly broad, likely overestimating the incidence of vaccine-induced myocarditis to an unknown degree. Additionally, there was no control group used to adjust for baseline myocarditis incidence in the study population. Importantly, it is misleading to compare the incidence of CAE reports with 120-day COVID-19 hospitalization rates. Preliminary evidence suggests that the clinical course of vaccine-associated myocarditis is mild; the clinical course of COVID-related hospitalization is quite serious for a minority of children (with nearly one quarter requiring ICU admission). Additionally, the use of a 120-day window understates ongoing risks posed by SARS-CoV-2 infection; vaccine protection against infection continues beyond the window, and pediatric COVID-19 hospitalization rates have continued to increase.

    Value added

    A recent MMWR report (Gargano et. al 2021) contained a similar analysis but with outcome data that was subject to physician review and adjudication for alternative myocarditis etiologies. It is not clear what this study adds to the previous report other than further age stratification.

  3. ScreenIT

    SciScore for 10.1101/2021.08.30.21262866: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableWe searched the Vaccine Adverse Event Reporting System (VAERS) data for females and males ages 12-17 in reports processed from 1/1/2021 through 6/18/2021 with diagnoses of “myocarditis,” “pericarditis,” “myopericarditis” or “chest pain” in the symptom notes and required the term “troponin” in the laboratory data.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were analyzed using Microsoft PowerBI, Stata and Microsoft Excel
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

  4. Version 1 published on medRxiv