Flexible Positive Airway Pressure Improves Treatment Adherence Compared with Auto-adjusting PAP
Bibliographic record
Abstract
STUDY OBJECTIVES: There are no clinical data comparing adherence and quality of life between auto-adjusting positive airway pressure (APAP) and two different flex positive airway pressure (PAP) devices (A-Flex, C-Flex) in patients with obstructive sleep apnea (OSA). DESIGN AND SETTING: Ninety-three patients in whom OSA was newly diagnosed were randomly assigned to receive 3 mo of APAP (n = 31), APAP with C-Flex (n = 31), or APAP with A-Flex (n = 31). Objective adherence was determined after 3 mo of CPAP treatment, and the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), and Calgary Sleep Apnea Quality of Life Index (SAQLI) were examined at baseline and after 3 mo. After 3 mo, patients in the APAP with A-Flex group and those in the APAP with C-Flex group were crossed over and those in the APAP group were switched to A-Flex for an additional 3 mo. MEASUREMENTS AND RESULTS: The groups were similar demographically. Treatment adherence during the first 3 mo was significantly greater in the APAP with C-Flex group (APAP with C-Flex: 5.19 ± 1.84 h/night versus APAP: 3.96 ± 1.66 h/night versus APAP with A-Flex: 4.27 ± 2.12 h/night, P = 0.04). There was a significant improvement in two of four of the SAQLI domain scores and in the ESS and PSQI in the APAP with C-Flex group. Adherence significantly improved among the poor compliers (< 4 h/night of use) in the APAP group after change to APAP with A-Flex (P = 0.01). CONCLUSIONS: Of these three modes of PAP delivery, adherence was greatest with APAP with C-Flex. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00873977.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".