Effects of cold temperature and snowfall on stroke mortality: A case-crossover analysis
Bibliographic record
Abstract
BACKGROUND: We sought to determine if cold temperature and snowfall are independently associated with stroke mortality, and whether effects differ between hemorrhagic and ischemic stroke. MATERIALS AND METHODS: We conducted a case-crossover study of 13,201 stroke deaths utilizing weather records between the months of November and April for Quebec, Canada from 1981 to 2015. We compared exposure to cold temperature and snowfall with controls days when stroke death did not occur. We computed odds ratios (OR) and 95% confidence intervals (CI) for the association of minimum temperature and duration of snowfall with stroke, adjusted for change in barometric pressure and relative humidity. RESULTS: The likelihood of mortality the day following exposure to cold temperature was elevated for hemorrhagic stroke in men, independent of snowfall. Relative to 0 °C, a temperature of -20 °C was associated with 1.17 times the odds of hemorrhagic stroke death (95% CI 1.04-1.32). An independent effect of snowfall was also present in men, with 12 h of snowfall associated with 1.12 times the odds of hemorrhagic stroke death (95% CI 1.00-1.24) compared with no snowfall. There was no evidence of an increased risk in women. Cold temperature and snowfall were not associated with ischemic stroke death in either men or women. CONCLUSION: Our results suggest that cold temperature and snowfall are independent risk factors for death from hemorrhagic stroke in men. These findings imply that interventions to prevent fatal hemorrhagic stroke during winter should include both cold temperature exposure and snowfall in men.
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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) | 0.005 | 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".