Abstract 13688: Association Between Daylight Saving Time and Acute Myocardial Infarction in Canada
Bibliographic record
Abstract
Background: Recent studies have suggested an increased risk of 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 PCI. Patients aged ≥18 years hospitalized between 2018 and 2022 were included. The primary endpoint was the incidence of AMI two weeks following DST transitions. The secondary endpoint was infarct size by biomarker assessment and LVEF. Results: 1142 charts were reviewed with 775 patients meeting the inclusion criteria (244 in the study group and 531 in the control group). Baseline clinical characteristics were comparable between both groups. (Table 1) The rate of AMI per day following DST transitions was 1.74 compared to 1.90 during control periods. DST was not associated with an increase in AMI (IRR = 0.92, 95% CI 0.79 - 1.07, p = 0.295). (Table 2) During the spring shift, the IRR was 0.83, p = 0.106, and during the autumn shift, the IRR was 1.01, p = 0.933. The rate of AMI was higher on the first day following DST, but it did not reach statistical significance (rate of AMI per day = 2.00; IRR = 1.05; p = 0.845). The transition to DST was not associated with a larger infarct size by CK-MB assessment, but LVEF was significantly slightly higher following DST transitions (LVEF 50 ± 11 % vs 48 ± 10 %, p = 0.038). Conclusion: In this cohort of Canadian patients, there was no significant association between DST transitions and the incidence of AMI. LVEF was higher following DST transitions, but infarct size was similar between study and control groups.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".