0557 Possible Contributory and Protective Factors in Medication Associated Obstructive Sleep Apnea (OSA): Results from the US Food and Drug Administration (FDA) Adverse Events Reporting System (FAERS)
Bibliographic record
Abstract
Abstract Introduction There are conflicting opinions regarding the role of medications in OSA. A Vigibase (WHO pharmacovigilance database) study (Linselle M, 2017) has suggested several drug groups in OSA pathogenesis. Sodium oxybate, benzodiazepines and opioids are most consistently associated with OSA. We examined the adverse drug reaction (ADR) of OSA with the ‘primary suspect’ drugs for the ADR, in the US Food and Drug Administration Adverse Events Reporting System (FAERS) database. Methods The FAERS database from January 1, 2004-March 31, 2019 (total ISR =12,330,939) was examined for Individual Safety Reports (ISR) with OSA as ADR and associated ‘primary suspect (PS)’ medications. Reporting odds ratios (ROR) were calculated to assess disproportionality signals with the ‘PS’ drug and OSA versus the ‘PS’ drug associated with all other ADRs in the database. Results 15,316 ISR were associated with OSA [mean±SD age: 49.21 ± 21.76 years (based on 10,311 ISR); 53.78% female (based on 12,274 ISR]. Increased disproportionality signals for OSA were detected with some of the following ‘PS’ drugs/drug groups: sodium oxybate [ROR=31.75, (95% CI 30.36-33.20)]; rofecoxib [ROR=7.85 (95% CI 7.40-8.32)], alendronate [ROR=3.60 (95% CI 3.37-3.84)], zoledronic acid [ROR=24.70 (95% CI 21.88-27.89)], omalizumab [ROR=2.36 (95% CI 2.09-2.68)], quetiapine [ROR=3.78 (95% CI 3.32-4.30), finasteride [ROR=6.03 (95% CI 5.17-7.04), pregabalin [ROR=1.19 (95% CI 1.01-1.41), isotretinoin [ROR=1.49 (95% CI 1.23-1.80)], ondansetron [ROR=3.35 (95% CI 2.77-4.06), olanzapine [ROR=2.64 (95% CI 2.17-3.20), sitagliptin [ROR=3.46 (95% CI 2.82-4.24, digoxin [ROR=2.83 (95% CI 2.24-3.57), benzodiazepines [ROR=1.80 (95% CI 1.33-2.42), and opioids [ROR=1.34 (95% CI 1.09-1.67)]. A decreased disproportionality signal was detected with several biologics including: adalimumab [ROR=0.87 (95% CI 0.79-0.95)], etanercept [ROR=0.55 (95% CI 0.49-0.61)], and infliximab [ROR=0.51 (9% CI 0.40-0.65)]. Conclusion The FAERS data supports many of the earlier findings suggesting the heterogeneity of medications associated with OSA. Biologics (mainly TNF-alpha antagonists) were associated with the previously unreported finding of a decreased OSA risk. Support None.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".