Obstructive Sleep Apnea as an Independent Stroke Risk Factor
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Stroke is a leading cause of death and disability affecting nearly 800,000 people in the United States every year. Obstructive sleep apnea (OSA) is found in over 60% of patients with stroke/transient ischemic attack (TIA) and identified as an independent stroke risk factor in large epidemiology studies and Canadian Stroke Prevention Guidelines (SPG) but not in the United States. The 2014 Secondary SPG recommend OSA screening and treatment as a consideration only, not a requirement. The twofold purpose of this article is, first, to present the evidence supporting OSA as an independent stroke risk factor in national SPG with mandatory recommendations and, second, to engage neuroscience nurses to incorporate OSA assessment and interventions into the nursing process and thereby promote excellence in stroke/TIA patient care. METHODS: A systematic literature search was conducted in Medline, CINAHL, and PubMed to identify research from 2003 through 2013 on the independent risk, mortality, and prevalence relationship between OSA and stroke/TIA including recurrence and recovery outcomes with continuous positive airway pressure (CPAP) therapy. RESULTS: Twenty-eight research articles were reviewed: 14 observational cohorts, five case-control studies, four cross-sectional studies, and four randomized control trials representing 12 countries and 10,671 subjects. DISCUSSION: OSA is highly prevalent in patients with stroke/TIA independently increasing stroke risk. CPAP studies revealed reduced stroke recurrence and improved recovery with feasible initiation in stroke units. Patients with stroke/TIA have less OSA-associated daytime sleepiness and obesity, making the usual screening tools insufficient and CPAP adherence challenging. Treating OSA decreases stroke prevalence and mortality. OSA initiatives empower neuroscience nurses to integrate this OSA evidence into clinical practice and improve stroke/TIA patient outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it