Comparative Analysis of Patients With STEMI and COVID-19 Between Canada and the United States
Bibliographic record
Abstract
Background Important health care differences exist between the United States (US) and Canada, which may have been exacerbated during the pandemic. We compared clinical characteristics, treatment strategies, and clinical outcomes of patients with ST-segment elevation myocardial infarction (STEMI) and COVID-19 (STEMI-COVID) treated in the US and Canada. Methods The North American COVID-19 Myocardial Infarction registry is a prospective, investigator-initiated study enrolling patients with STEMI with confirmed or suspected COVID-19 in the US and Canada. The primary end point was in-hospital mortality. Additionally, we explored associations between vaccination and clinical outcomes. Results Of 853 patients with STEMI-COVID, 112 (13%) were enrolled in Canada, and compared with the US, patients in Canada were more likely to present with chest pain and less likely to have a history of heart failure, stroke/transient ischemic attack, pulmonary infiltrates or renal failure. In both countries, the primary percutaneous coronary intervention was the dominant reperfusion strategy, with no difference in door-to-balloon times; fibrinolysis was used less frequently in the US than in Canada. The adjusted in-hospital mortality was not different between the 2 countries (relative risk [RR], 1.0; 95% CI, 0.46-2.72; P = 1.0). However, the risk of in-hospital mortality was significantly higher in unvaccinated compared with vaccinated patients with STEMI-COVID (RR, 4.7; 95% CI, 1.7-11.53; P = .015). Conclusions Notable differences in morbidities and reperfusion strategies were evident between patients with STEMI-COVID in the US compared with Canada. No differences were noted for in-hospital mortality. Vaccination, regardless of region, appeared to associate with a lower risk of in-hospital mortality strongly.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".