Quality of life among sleep apnea patients before and after treatment with continuous positive airway pressure (CPAP) compared to controls from the general population
Bibliographic record
Abstract
The aim of this study was to compare health-related quality of life between patients with obstructive sleep apnea (OSA) and subjects from the general population. Also, the change in quality of life with CPAP treatment was explored. The OSA subjects (n=822) were untreated newly diagnosed with moderate or severe OSA. The control subjects (n=742) were randomly selected Icelanders ≥40 years old. Quality of life was measured by the Short Form 12 (SF-12) which gives a physical component score (PCS) and mental component score (MCS). Scoring are transformed into a scale ranging from 0 (worst possible health) to 100 (best possible health).The change with CPAP treatment was assessed after two years and 90.1% (n=741) of the OSA subjects finished the follow up. Untreated OSA patients reported worse quality of life than controls (mean PCS 40.1±10.9 vs. 50.7±8.0 for controls (p<0.0001) and mean ± MCS 48.4±10.9 vs. 51.4±4.7 for controls (p<0.0001)). Among OSA patients, both mental and physical health improved from baseline to follow up (mean change for PCS = 2.57±9.4 and for MCS = 2.37 ± 11.12). Altogether, 64% of OSA patients were using CPAP at the follow up and most of them were full users. Among CPAP users, there was an increase in MCS of 2.6 ± 11.1 vs. 1.9 ± 11.3 among non-users and in PCS of 3.0 ± 9.0 vs. 1.8 ± 10.2 among non-users. The difference between users and non-users was however non significant. OSA patients report severely impaired quality of life compared to controls. Both physical and mental health improve from baseline to follow up for OSA patients but the improvement is not significantly greater among CPAP users.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".