Auto-Titrating Versus Standard Continuous Positive Airway Pressure for the Treatment of Obstructive Sleep Apnea: Results of a Meta-analysis
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Bibliographic record
Abstract
STUDY OBJECTIVE: To compare the effectiveness of auto-titrating continuous positive airway pressure (APAP) versus conventional continuous positive airway pressure (CPAP) in reducing the apnea-hypopnea index (AHI), reducing the mean airway pressure, improving subjective sleepiness, and improving treatment adherence in patients with obstructive sleep apnea (OSA). DESIGN: Meta-analysis and metaregression of published randomized trials comparing APAP to CPAP. SETTING: N/A. PARTICIPANTS: N/A. INTERVENTIONS: N/A. RESULTS: We identified 9 randomized trials studying a total of 282 patients. Compared to CPAP, there was no significant advantage of APAP in reducing AHI or sleepiness (pooled APAP-CPAP posttreatment AHI and Epworth Sleepiness Scale score = -0.20 events per hour, 95% confidence interval:[-0.74,0.35], and -0.56 [-1.4,0.3] respectively). The use of APAP reduced the mean applied pressure across the night by 2.2 cm water [1.9,2.5] compared to CPAP. Adherence with therapy was not substantially improved with APAP; pooled estimate of improvement was 0.20 hours per night ([-0.16,0.57], P = .28) using a random-effects model. CONCLUSIONS: Compared to standard CPAP, APAP is associated with a reduction in mean pressure. However, APAP and standard CPAP were similar in adherence and their ability to eliminate respiratory events and to improve subjective sleepiness. Given that APAP is more costly than standard CPAP, APAP should not be considered first-line chronic therapy in all patients with OSA. However, APAP may be useful in other situations (eg, home titrations, detection of mouth leak) or in certain subgroups of patients with OSA. Identifying circumstances in which APAP is a definite improvement over CPAP in terms of costs or effects should be the focus of future studies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it