A new tool to help patients with obstructive sleep apnea syndrome (OSAS) make informed therapeutic choices
Bibliographic record
Abstract
There remains concern that patients may not be fully informed regarding their mechanical treatment options for OSAS: continuous positive airway pressure (CPAP) or oral appliance (OA). Objective: To develop a tool to help clinicians inform patients about treatment options, and to assess its validity, reliability and acceptability. Methods: We developed a decision board (DB), to present information regarding the potential benefits and side effects of the 2 treatment options, using the best available evidence. To test validity, we evaluated in 34 healthy volunteers the extent to which the respondents' preferences for a treatment changed predictably when the rate of effectiveness and side-effects were modified. Reliability was tested by re-administering the DB 2 weeks after (kappa test). The DB acceptability was evaluated in 68 consecutive patients newly diagnosed with OSAS, AHI=39 (22). Results: In healthy volunteers, 58.8% chose OA, 41.2% chose CPAP. In the former group, 85% switched preference when the rate of effectiveness was reduced from 6/10 to 3/10, and 90% when the occurrence of occlusal contacts modification increased from 4/10 to 8/10. In the CPAP group, 57% switched when effectiveness was reduced from 10/10 to 5/10, and 42% when non compliance due to adverse effects increased from 3/10 to 6/10. Reliability was excellent (k=0.94). Concerning acceptability, 90% of the patients were satisfied with the information provided in the DB and 88% indicated that it helped them make a decision. The average score of true/false test of comprehension was 7.9 of 10 (range, 4 to 10). Conclusion: The DB is a valid, reliable and acceptable tool to assess OSAS patients' preferences.
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".