Risk of acute myocardial infarction, stroke and thromboembolism following COVID-19 vaccination compared to testing positive for COVID-19 infection: a nationwide cohort study of 4.6 mio individuals
Bibliographic record
Abstract
Abstract Background Large randomized controlled trials (RCT) have shown that COVID-19 vaccines are effective at preventing severe COVID-19. However, the RCT's are not powered to detect rare adverse events. It has been reported that the new mRNA based COVID-19 vaccines may increase the risk of thromboembolic and ischemic events. Likewise, thromboembolic and ischemic events are also known complications to infection with SARS-CoV-19. Currently, less is known about the risk-reward relationship of receiving an mRNA-based COVID-19 vaccine versus contracting COVID-19 infection with respect to thromboembolic and ischemic outcomes. Purpose To compare the risk of thromboembolic and ischemic events following COVID-19 vaccination to the risk following infection with SARS-CoV-19. Methods The study period was from March 2020 to August 2021. All individuals were >18 years old. The population was stratified into two different groups. The vaccinated group consisted of recipients of the first dose of either Moderna (mRNA-1273, n=488,220) or Pfizer-BioNTech (BNT162b2 mRNA, n=3,186,164) vaccines. Individuals who had previously tested positive for SARS-CoV-19 were excluded. The other group consisted of individuals who had tested positive for SARS-CoV-19 in the same period who had not yet received their first vaccination dose (n=233,926). The exposure period for both groups was set to 28 days following vaccination/testing positive for SARS-CoV-19 (Figure 1). Patient level data were obtained on all included individuals using nationwide registries. Primary outcomes were acute myocardial infarction (AMI), ischemic stroke, pulmonary embolism (PE), and deep venous thrombosis (DVT). Odds ratios were obtained from logistic regression models with the vaccinated group acting as reference. Multivariable models were adjusted for demographics and comorbidities. Results In the vaccinated group, mean age was 53±19 years and 50.3% were female. In the group of participants testing positive for SARS-CoV-19, mean age was 42.1±17.4 years and 50.2% were female. In total, 773 suffered a stroke, 472 suffered a PE, 500 suffered an AMI, and 484 suffered a DVT during the 28-day exposure period. We observed an increased absolute risk of all outcomes for participants testing positive for SARS-CoV-19 as compared to participants being vaccinated (stroke: 0.049% vs 0.019%, p<0.001), (PE: 0.91% vs 0.0072%, p<0.001), (AMI: 0.021 vs 0.013, p=0.0004), and (DVT: 0.037% vs 0.011%, p<0.001). In multivariable models, participants testing positive for SARS-CoV-19 had a significantly increased risk of all outcomes compared to participants being vaccinated: (stroke: OR: 4.0, 95% CI: [2.9–5.6], p<0.001), (PE: OR: 38.6 95% CI: [30.3–48.5], p<0.001), (AMI: OR: 3.3, 95% CI: [2.1–5.00], p<0.001), and (DVT: OR: 5.3, 95% CI: [3.8–7.5], p<0.001) (Figure 2). Conclusion The risks of thromboembolic and ischemic events were substantially higher after SARS-CoV-19 infection than after vaccination in the Danish population. Funding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Gentofte University Hospital
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".