Prognostic Impact of Obstructive Sleep Apnea in Patients Presenting with Acute Symptomatic Pulmonary Embolism
Bibliographic record
Abstract
Abstract Background In patients with pulmonary embolism (PE), there is a lack of comprehensive data on the prevalence and prognostic significance of pre-existing obstructive sleep apnea (OSA). Methods In this study of patients with PE from the Registro Informatizado de la Enfermedad TromboEmbólica (RIETE) registry, we assessed the prevalence of OSA, and the association between pre-existing OSA and the outcomes of all-cause mortality, PE-related mortality, recurrences, and major bleeding over 30 days after initiation of PE treatment. Additionally, we also examined rates of outcomes within 90 days and 1 year following the diagnosis of PE. Results Of 4,153 patients diagnosed with PE, 241 (5.8%; 95% confidence interval [CI]: 5.1–6.6%) had pre-existing OSA. Overall, 166 (4.0%; 95% CI: 3.4–4.6%) died during the first 30 days of follow-up. In multivariable analysis, the OSA syndrome was not a significant predictor of death from any cause (odds ratio [OR]: 1.5; 95% CI: 0.8–2.9; p = 0.19). However, patients with pre-existing OSA had an increased PE-specific mortality (adjusted OR: 3.0; 95% CI: 1.3–6.8; p = 0.01) compared with those without OSA. OSA was not significantly associated with 30-day recurrent venous thromboembolism (adjusted OR: 0.6; 95% CI: 0.1–4.7; p = 0.65) or major bleeds (adjusted OR: 1.0; 95% CI: 0.4–2.2; p = 1.0). Findings were similar at 90-day and 1-year follow-ups. Conclusion In patients presenting with PE, pre-existing OSA is relatively infrequent. Patients with OSA were at increased risk of PE-related mortality when compared with those without OSA.
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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 | 0.000 | 0.004 |
| 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 | 0.001 | 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".