O079 The effect of long-term CPAP on subclinical markers of coronary artery disease in clinic patients with OSA
Bibliographic record
Abstract
Abstract Background In view of the current uncertainty about the relationship between obstructive sleep apnoea (OSA) and development of major adverse cardiovascular events (MACE) we studied the long-term effect of continuous positive airway pressure (CPAP) on important subclinical markers known to be on the causal pathway to coronary artery disease (CAD) Methods We used our database of sleep clinic patients (n=4,226) who had baseline phenotypic assessments, between 2006 and 2010, including level 1 polysomnography to determine the presence and severity of OSA. We performed follow-up assessments between 2019-22 on 2 groups of consenting participants who were alive and free of MACE at baseline and during the follow-up period: those with long-term good CPAP use and those with poor or no use. We will compare follow-up High sensitivity Troponin-I and coronary calcium scores between groups, using propensity score matching methods. Progress to date A total of 263 patients completed follow-up assessments and will undergo propensity score matching. Of these, 134 had good CPAP use and 129 had no or poor CPAP use. The two groups had similar baseline characteristics: median age 62 vs 60 years, male 67% vs 64%, body-mass-index 32.6 vs 30.0kg/m2 respectively. Intended outcome and impact This project is intended to provide further insight into the relationship between OSA and risk for developing CAD, by studying the effect of long-term good CPAP use, compared to no or poor CPAP use, on changes in established sub-clinical biomarkers of coronary disease.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".