Bibliographic record
Abstract
TOPIC IMPORTANCE: Stroke is the second-leading cause of death worldwide. OSA is an independent risk factor for stroke and is associated with multiple vascular risk factors. Poststroke OSA is prevalent and closely linked with various stroke subtypes, including cardioembolic stroke and cerebral small vessel disease. Observational studies have shown that untreated poststroke OSA is associated with an increased risk of recurrent stroke, mortality, poorer functional recovery, and longer hospitalizations. REVIEW FINDINGS: Poststroke OSA tends to be underdiagnosed and undertreated, possibly because patients with stroke and OSA present atypically compared with the general population with OSA. Objective testing, such as the use of ambulatory sleep testing or in-laboratory polysomnography, is recommended for diagnosing OSA. The gold standard for treating OSA is CPAP therapy. Randomized controlled trials have shown that treatment of poststroke OSA using CPAP improves nonvascular outcomes such as cognition and neurologic recovery. However, findings from randomized controlled trials that have evaluated the effect of CPAP on recurrent stroke risk and mortality have been largely negative. SUMMARY: There is a need for high-quality randomized controlled trials in poststroke OSA that may provide evidence to support the utility of CPAP (and/or other treatment modalities) in reducing recurrent vascular events and mortality. This goal may be achieved by examining treatment strategies that have yet to be trialed in poststroke OSA, tailoring interventions according to poststroke OSA endotypes and phenotypes, selecting high-risk populations, and using metrics that reflect the physiologic abnormalities that underlie the harmful effects of OSA on cardiovascular outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".