A Pilot Study of Aspirin Resistance in Obstructive Sleep Apnea Patients
Bibliographic record
Abstract
Purpose: Obstructive sleep apnea (OSA) leads to endothelial dysfunction and platelet hyperactivity, which are linked to increased risk of cardiovascular disease and implicated in the development of aspirin resistance. We hypothesized that aspirin resistance is prevalent among OSA patients and aimed to explore effects of continuous positive airway pressure (CPAP) therapy on aspirin responsiveness. Methods: In Phase 1, prevalence of aspirin resistance was determined cross-sectionally in a group of OSA patients (n=59) on daily low-dose aspirin (81 mg) taken before entering the study, for primary or secondary prevention. In Phase 2, aspirin responsiveness before and after initiation of CPAP therapy was compared and stratified by endothelial function in a cohort of aspirin-naïve patients with newly diagnosed OSA (n=18). Results: In Phase 1, prevalence of aspirin resistance was 17%; most patients (56%) were on CPAP therapy. In Phase 2, initiation of CPAP therapy was associated with significant improvement in endothelial function (p=0.03). The mean pre-CPAP aspirin resistance units (ARU) was 569 (SD=75). In subjects with endothelial dysfunction (44%), the mean decrease after initiation of CPAP therapy was 43 ARU (SD=81, p=0.18). In contrast, subjects with normal endothelial function experienced the mean decrease of 8 ARU (SD=116, p=0.83). Conclusion: Aspirin resistance may be prevalent among OSA patients. After initiation of CPAP therapy, we observed a trend towards improvement in aspirin responsiveness among patients with endothelial dysfunction. The role of endothelial dysfunction and aspirin resistance should be explored in further studies that focus on the effect of CPAP 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".