Sleep Patterns and the Risk of Acute Stroke
Bibliographic record
Abstract
Background and Objectives: Symptoms of sleep disturbance are common, and may represent important modifiable risk factors for stroke. We evaluated the association between a spectrum of sleep disturbance symptoms and risk of acute stroke in an international setting. Methods: INTERSTROKE is an international case-control study of patients presenting with first acute stroke and controls matched by age (+/- 5 years) and sex. Sleep symptoms in the previous month were assessed via a questionnaire. Conditional logistic regression estimated the association between sleep disturbance symptoms and acute stroke, expressed as odds ratios and 95% confidence intervals. The primary model adjusted for age, occupation, marital status and modified-Rankin Scale at baseline, with subsequent models adjusting for potential mediators (behavioural/disease risk factors). Results: Overall, 4,496 matched participants were included, with 1,799 of participants having experienced an ischemic stroke and 439 an intracerebral haemorrhage. Short sleep (<5hrs: 3.15, 2.09-4.76), long sleep (>9hr: 2.67, 1.89-3.78), impaired quality (1.52, 1.32-1.75), difficulty getting to sleep (1.32, 1.13-1.55) or maintaining sleep (1.33, 1.15-1.53), unplanned napping (1.59, 1.31-1.92), prolonged napping (>1hr: 1.88, 1.49-2.38), snoring (1.91, 1.62-2.24), snorting (2.64, 2.17-3.20) and breathing cessation (2.87, 2.28-2.60) were all significantly associated with increased odds of acute stroke in the primary model. A derived Obstructive Sleep Apnoea (OSA) score of 2-3 (2.67, 2.25-3.15) and cumulative sleep symptoms (>5: 5.06, 3.67-6.97) were also associated with a significantly increased odds of acute stroke, with the latter showing a graded association. Following extensive adjustment, significance was maintained for the majority of symptoms (not difficulty getting to/maintaining sleep and unplanned napping), with similar findings for stroke subtypes. Discussion: We found that sleep disturbance symptoms were common, and associated with a graded increased risk of stroke. These symptoms may be a marker of increased individual risk, or represent independent risk factors. Future clinical trials are warranted to determine the efficacy of sleep interventions in stroke prevention.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".