Comparison of the phenotypic characteristics between responders and non-responders to obstructive sleep apnea treatment using mandibular advancement devices in adult patients: Systematic review and meta-analysis
Bibliographic record
Abstract
Mandibular advancement device (MAD) therapy is the most commonly used second-line treatment for obstructive sleep apnea (OSA), but MAD may be ineffective in a subgroup of patients. The aim of this systematic review is to identify predictors of the efficacy of oral appliance (OA) therapy for OSA in adult patients. This review focuses on performing the quantitative analysis by subgroups based on the response criteria used in the literature and based on the type of device. PubMed, EMBASE, Scopus, Web of Science and Cochrane databases was conducted to identify potentially relevant studies published until Dec 2021. The search identified 1343 preliminary references. A total of 99 studies met the eligibility criteria and were included in the review, and 60 in the meta-analysis. The quality of studies was assessed using the Newcastle-Ottawa scale and the Cochrane scale. Based on meta-analysis, and considering a low to moderate evidence profile according to the GRADE scale, responders are younger patients, with smaller neck circumference, lower body mass index. Responders have shorter maxillary length, lower anterior and posterior facial height, a shorter distance from the hyoid bone to the third cervical vertebra, a shorter airway length, a smaller minimum airway cross-sectional area and a higher minimum oxygen saturation during sleep. Responders needed a lower optimal continuous positive airway pressure than non-responders. The type of device has not affected the results of the meta-analysis. The criterion "AHI <10 and reduction AHI >50%" is the one that provides the "weight" of significance for several variables. This criterion should be taken into consideration for future studies to predict OSA treatment by OA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".