Outcome Reporting in Prospective Studies Evaluating Neurostimulation for Obstructive Sleep Apnea
Bibliographic record
Abstract
OBJECTIVE: Due to the controversy surrounding the appropriate outcomes in neurostimulation, we sought to systematically describe ways in which polysomnography and apnea-hypopnea index are reported in prospective studies involving unilateral hypoglossal nerve stimulation. DATA SOURCES: MEDLINE (Ovid), Embase (Ovid), Cochrane Library, and Scopus. REVIEW METHODS: Following the Preferred Reporting items of Systematic Reviews and Meta-analysis (PRISMA) Statement guidelines, a systematic two-reviewer system was used for study screening and quality assessment. Articles that met inclusion criteria were included. Quality was evaluated with either the Newcastle-Ottawa Quality Assessment Scale or the Covidence risk-of-bias tool. RESULTS: Fifteen studies met the inclusion criteria, which included 14 prospective cohort studies and one randomized controlled trial. Titration polysomnography was the primary sleep study used to acquire data in five of the studies compared to only three studies employing exclusively non-titration polysomnography to report outcomes. Three studies compiled data from two or more sleep studies to report a single apnea-hypopnea index. Within the 15 studies, non-titration apnea-hypopnea index was the most reported type (five studies). Titration apnea-hypopnea index was used to report outcomes in one study. Five studies did not specify what type of apnea-hypopnea index was employed to report treatment effectiveness. CONCLUSION: The reported sleep studies and corresponding apnea-hypopnea indices were highly variable across the studies. Because of the high degree of heterogeneity, future research would benefit from consistent use of a standardized apnea-hypopnea index to report outcomes related to hypoglossal nerve stimulation. LEVEL OF EVIDENCE: NA Laryngoscope, 134:4873-4881, 2024.
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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 | 0.259 | 0.521 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.017 |
| Bibliometrics | 0.015 | 0.019 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".