Obstructive sleep apnea (OSA) in elderly patients. Role of continuos positive airway pressure (CPAP) treatment. A multicenter randomized controlled clinical trial
Bibliographic record
Abstract
OBJECTIVE: To analyze the effect of CPAP treatment on various clinical variables, Quebec sleep questionnaire(QSQ),and neurocognitive tests in elderly patients who have a severe OSA (AHI≥30) . METHODS: A multicenter, randomized, controlled, clinical trial in a consecutive cohort of patients ≥ 70 years old with severe OSA to receive or not receive CPAP. Anthropometric data , clinical records, OSA related clinical symptoms, QSQ, neurocognitive, anxiety and depression ( HADS) tests were collected. Patients were monitored 3 times during the study, including variable measurements at the beginning and at 3 months. It was felt that there was good adherence to. The intragroup and intergroup comparison was performed jointly using an ANCOVA test on an intention to treat analysis (ITT). RESULTS: We randomized 214/285 elderly patients (105 CPAP and 109 not CPAP). There were no significant differences between baseline variables of the randomized groups. Mean age was 76 (4) years, 69% were men. The mean AHI was 50 (15) and 38% presented daytime sleepiness. The average use of CPAP was 4.9 (2.5) hours, with 69% patients with good adherence (CPAP ≥ 4h/night). CPAP group achieves a greater improvement in all quality of life domains (p<0.001), sleep-related symptoms (all p<0.001), as well as anxiety (p=0.016) and depression (p<0.001) indexes and digital symbol test (p=0.047). CONCLUSIONS: In elderly patients with severe OSA, CPAP treatment resulted in an improvement in quality of life, sleep-related symptoms, anxiety and depression indexes and some neurocognitive aspects.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".