Reconsidering first-line treatment for obstructive sleep apnea: A systematic review of the literature
Bibliographic record
Abstract
BACKGROUND: Continuous positive airway pressure (CPAP) is typically recommended as first line therapy for obstructive sleep apnea, but the adherence rate of CPAP is problematic. This study's objective was to systematically review the literature relating to CPAP as first line therapy for OSA and compare it to surgical literature on the same topic. METHODS: A systematic review was conducted according to PRISMA guidelines, examining Medline-Ovid, Embase, and Pubmed databases. The primary search objective was to identify all papers reporting the results of (1) randomized clinical trials (RCT) of CPAP for the treatment of adults with OSA; and (2) both randomized and non-randomized clinical trials and case series on the surgical treatment of OSA in adults. A PhD-level biostatistician first screened papers, and then those that met study criteria were retrieved and analyzed using standardized forms for each author. The primary outcomes were adherence rates of CPAP. RESULTS: A total of 82 controlled clinical trials for CPAP and 69 controlled and non-controlled surgery trials were identified for analysis. Variation in CPAP use within reported RCT trials were identified, and the majority of patients in the studies would eventually be considered non-adherent to CPAP. CONCLUSIONS: When considering the numerous patient-related factors that come into play when CPAP is prescribed, the concept of CPAP as gold-standard therapy for OSA should be reconsidered. In many cases surgery can provide a better overall outcome. This study's results suggest that certain patients with OSA may be managed more effectively with surgery than CPAP, without confounding issues of treatment adherence.
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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 | 0.019 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".