Efficacy of an oral appliance for the treatment of obstructive sleep apnea in a Brazilian population
Bibliographic record
Abstract
Aim: the aim of this prospective study was to validate, in Brazil, the use of an MRA to treat OSA and primary snoring, comparing polysomnographic and Epworth Sleepiness Scale (ESS) data obtained prior to and during MAS treatment. Method: this study was carried out on 63 patients presented with different OSA severity or primary snoring, who were fitted to PMPositioner® between 2009 and 2011. The diagnosis was established by a polysomnogram (PSG) prior treatment and a PSG after 6 month verified the efficacy of MRA therapy. Subjective daytime sleepness was evaluated by ESS questionnaire prior to treatment and at the follow up. Results: The sample was divided in primary snoring and OSA group. For the primary snoring group, PSG variables did not show significant results, except for snoring decreasing. For the OSA group the mean AHI has reduced from 23.0±11 to 5.3±4.0 (p≤0.001) and median ESS reduced significantly from 13.0(3-24) to 8.5(3-13). Complete response (AHI<5.0) was found in 25 (40%) of the patients; partial response (AHI ≤10) was found in 27 (43%) patients. Conclusion: The findings of the present study validate the efficacy of the adjustable PM Positioner® for the treatment of OSA in Brazilian patients. This appliance can provide safe treatment for 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 | 0.000 | 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 | 0.000 | 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".