0575 ATTITUDES TOWARDS ACCEPTANCE OF OBSTRUCTIVE SLEEP APNEA THERAPY USING UPPER AIRWAY MUSCLE TRAINING
Bibliographic record
Abstract
Attitudes towards acceptance of obstructive sleep apnea therapy using upper airway muscle training 158 consecutive newly diagnosed OSA patients were recruited to complete a self-administered questionnaire, including assessment of their interest towards UAMT, anticipated ability to complete such therapy, as well as information about factors that could influence these attitudes. Socio-demographic information and sleep recording data were also obtained. The majority of patients were interested in such program (82.9%) and mentioned their anticipated ability to complete it 1 hour/day for 1 month (72.1%), especially if applied later only 2–3 times/week (82.9%). 55.0% of them indicated that requirements of training schedule and duration might influence their choice. Patients with low Socioeconomic status (SES) or female gender were more prone to complete such program 2–3 times/week when compared to those with high SES or male subjects (p<0.05). Multivariate analysis revealed that age (OR: 1.04, 95% CI: 1.01–1.07; P=0.02) was an independent determinant for interest to complete UAMT therapy. ODI (OR: 0.95, 95% CI: 0.94–1.00; P=0.04) predicted preference for UAMT over the overnight-used conventional devices. This study demonstrates that the majority of OSA patients are interested in UAMT therapy, suggests their anticipated ability to complete it, along with a preference over conventional therapies. Attitudes towards such therapy are sensitive to factors such as gender, age, severity of OSA and SES level None.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".