Insomnia complaints in lean patients with obstructive sleep apnea negatively affect positive airway pressure treatment adherence
Bibliographic record
Abstract
Summary The objective of this study was to evaluate the determinants of long‐term adherence to positive airway pressure treatment among patients with obstructive sleep apnea, with special emphasis on patients who stop positive airway pressure treatment within 1 year. This is a prospective long‐term follow‐up of subjects in the Icelandic Sleep Apnea Cohort who were diagnosed with obstructive sleep apnea between 2005 and 2009, and started on positive airway pressure treatment. In October 2014, positive airway pressure adherence was obtained by systematically evaluating available clinical files (n = 796; 644 males, 152 females) with moderate to severe obstructive sleep apnea (apnea–hypopnea index ≥15 events per h). The mean follow‐up time was 6.7 ± 1.2 years. In total, 123 subjects (15.5%) returned their positive airway pressure device within the first year, 170 (21.4%) returned it later and 503 (63.2%) were still using positive airway pressure. The quitters within the first year had lower body mass index, milder obstructive sleep apnea, less sleepiness, and more often had symptoms of initial and late insomnia compared with long‐term positive airway pressure users at baseline. Both initial and late insomnia were after adjustment still significantly associated with being an early quitter among subjects with body mass index <30 kg m−2, but not among those with body mass index ≥30 kg m−2. The prevalence of early quitters decreased significantly during the study period (2005–2009). Almost two‐thirds of patients with moderate to severe obstructive sleep apnea are positive airway pressure users after 7 years. Obesity level, obstructive sleep apnea severity and daytime sleepiness are important determinants of long‐term adherence. Symptoms of initial and late insomnia are associated with early quitting on positive airway pressure among non‐obese subjects.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".