The Association Between Daylight Saving Time and Acute Myocardial Infarction in Canada
Bibliographic record
Abstract
Background: Recent studies have suggested an increased risk of acute myocardial infarction (AMI) following daylight saving time (DST) transitions in cohorts of American and European patients. We aim to validate this finding in a Canadian population. Methods: We performed a retrospective cohort study of patients admitted to the Hôpital du Sacré-Coeur de Montréal with a diagnosis of AMI requiring a coronary angiogram from 28 February 2016 to 3 December 2022. The transition period was defined as two weeks following DST, while the control periods were two weeks before and two weeks after the transition period. Patients aged 18 years or older were included. The primary endpoint was the incidence rate ratio (IRR) of AMI following DST transitions while the secondary endpoint was infarct size by biomarkers. A subgroup analysis compared the pre-COVID-19 period (2016–2019) to the post-COVID-19 period (2020–2022). Results: A total of 1058 patients were included (362 in the transition group and 696 in the control group). The baseline clinical characteristics were comparable between both groups. The rate of AMI per day following the DST transitions was 1.85 compared to 1.78 during control periods. The DST transitions were not associated with an increase in AMI (IRR = 1.04, 95% CI 0.91–1.18, p = 0.56) nor with infarct size. In the subgroup analysis, DST was associated with a significant increase in the incidence of AMI only in the pre-COVID-19 period, with a rate of 2.04 AMI per day in the transition group compared to 1.71 in the control group (IRR = 1.19, 95% CI 1.01–1.41, p = 0.041). In contrast, there was a significant increase in the size of AMI following DST in the post-COVID-19 period subgroup, with a creatine phosphokinase-MB (CK-MB) concentration of 137 ± 229 µg/L compared to 93 ± 142 µg/L (p = 0.013). Conclusions: In this Canadian cohort, there was a significant increase in the incidence of AMI in the pre-COVID-19 period, and infarct sizes were significantly larger following the DST transitions in the post-COVID-19 period. No significant associations emerged when pre- and post-COVID-19 periods were pooled.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".