Association of Sleep-disordered Breathing and the Occurrence of Stroke
Bibliographic record
Abstract
RATIONALE: Sleep-disordered breathing has been linked to stroke in previous studies. However, these studies either used surrogate markers of sleep-disordered breathing or could not, due to cross-sectional design, address the temporal relationship between sleep-disordered breathing and stroke. OBJECTIVES: To determine whether sleep-disordered breathing increases the risk for stroke. METHODS: We performed cross-sectional and longitudinal analyses on 1,475 and 1,189 subjects, respectively, from the general population. Sleep-disordered breathing was defined by the apnea-hypopnea index (frequency of apneas and hypopneas per hour of sleep) obtained by attended polysomnography. The protocol, including polysomnography, risk factors for stroke, and a history of physician-diagnosed stroke, was repeated at 4-yr intervals. MEASUREMENTS AND MAIN RESULTS: In the cross-sectional analysis, subjects with an apnea-hypopnea index of 20 or greater had increased odds for stroke (odds ratio, 4.33; 95% confidence interval, 1.32-14.24; p = 0.02) compared with those without sleep-disordered breathing (apnea-hypopnea index, <5) after adjustment for known confounding factors. In the prospective analysis, sleep-disordered breathing with an apnea-hypopnea index of 20 or greater was associated with an increased risk of suffering a first-ever stroke over the next 4 yr (unadjusted odds ratio, 4.31; 95% confidence interval, 1.31-14.15; p = 0.02). However, after adjustment for age, sex, and body mass index, the odds ratio was still elevated, but was no longer significant (3.08; 95% confidence interval, 0.74-12.81; p = 0.12). CONCLUSIONS: These data demonstrate a strong association between moderate to severe sleep-disordered breathing and prevalent stroke, independent of confounding factors. They also provide the first prospective evidence that sleep-disordered breathing precedes stroke and may contribute to the development of stroke.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".