CPAP compliance - A two year follow-up study: The Icelandic sleep apnea cohort (ISAC)
Bibliographic record
Abstract
Objectives: To estimate the main determinants of continuous positive airway pressure (CPAP) usage in a well defined population. Methods: Patients diagnosed with moderate to severe obstructive sleep apnea (OSA) in Iceland were invited to participate. Altogether 822 OSA patients participated (665 males, 157 females). Two years later they were invited for a follow-up evaluation. Results: Altogether 741 (90%) OSA patients returned for the 2 year follow-up. Of those, n=475 (64%) were using CPAP and n=266 were non-users. Of the nonusers, 17% had returned the device within 30 days, and altogether 30% had returned the device within 3 months. The average±SD use per night was 6.2±1.9 hours and only n=47 used CPAP < 4 h/night. At baseline, the users at two years had significantly higher BMI (34.1±5.6 vs. 32.4±5.6 kg/m 2 , p<0.0001) and a higher apnea hypopnea index (AHI) (48.5±21.0 vs. 38.6±17.9 events/h, p<0.0001). They also reported more sleepiness as measured by the Epworth Sleepiness Scale (ESS, 12.3±5.0 vs. 11.3±5.0, p=0.03). Among those with BMI>35 kg/ 2 and ESS >10, altogether 76% were using CPAP at the follow-up visit compared to 44% of those with BMI<30 and ESS<10, a significant interaction in logistic regression. Hypertensives were more likely to use CPAP (72%) at follow-up compared to nonhypertensives (58%), p<0.001, which remained significant after adjusting for AHI, BMI and sleepiness. Conclusion: Two-thirds of moderate to severe OSA patients are regular CPAP users after 2 years and the majority of them have high usage per night. Obesity, OSA severity, hypertension status and sleepiness are all important determinant of long-term compliance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".