Impact of CPAP Therapy Adherence on Global Cognition in Patients with Moderate to Severe Obstructive Sleep Apnea: A One-Year Follow-Up
Bibliographic record
Abstract
Background: Obstructive sleep apnea increases (OSA) cognitive impairment risk. The objective of this study was to determine the impact of continuous positive airway pressure (CPAP) adherence on global cognition using the Montreal Cognitive Assessment questionnaire (MoCA). Materials and Methods: Thirty-four new patients diagnosed with moderate or severe OSA (apnea-hypopnea index AHI ≥ 15 events/h) from the CPAP group were compared with thirty-one moderate to severe OSA patients from the no-CPAP group. In addition, all patients completed the MoCA test, a patient health questionnaire (PHQ-9) for depressive symptoms, and a generalized anxiety questionnaire (GAD-7) for anxiety symptoms, at baseline, after 6 months, and after 1 year. Results: At baseline, there were no significant differences between the two groups regarding total MoCA scores, 20.9 ± 3.5 CPAP group to 19.7 ± 2.9 no-CPAP group (p = 0.159), PHQ-9 (p = 0.651), and GAD-7 (p = 0.691). After one year, improvement was observed for a total MoCA score of 22.7 ± 3.5 (p < 0.001) for the CPAP group, and significant variance of score between groups was more accentuated for delayed recall and attention (p < 0.001) sub-topic. Moreover, PHQ-9, GAD-7 scores, and the Epworth Sleepiness Scale (ESS) decreased significantly (p < 0.001) after CPAP therapy. The MoCA score was significantly correlated with years of education (r = 0.74, p < 0.001) and had a negative correlation with body mass index (BMI) (r = −0.34), ESS (r = −0.30) and PHQ-9 (r = −0.34). Conclusions: One year of CPAP adherence improved global cognition associated with OSA.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".