Body Mass Index and Hypoglossal Nerve Stimulation Outcomes: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Objective This systematic review and meta‐analysis evaluated how body mass index (BMI) influences surgical outcomes of hypoglossal nerve stimulation (HGNS) for obstructive sleep apnea (OSA), specifically comparing patients with BMI ≥ 32 kg/m 2 to those with BMI < 32 kg/m 2 . Data Sources PubMed, Embase, and Scopus were searched from January 2014 to April 2025 for prospective and retrospective cohort studies or case–control studies reporting HGNS outcomes stratified by BMI. Review Methods Following PRISMA guidelines, data were extracted on study design, demographics, baseline apnea–hypopnea index (AHI), and postoperative outcomes. Surgical success was defined using Sher or modified Sher criteria. Random‐effects meta‐analysis was performed using the DerSimonian and Laird method. Fixed‐effect inverse‐variance weights were first calculated, and between‐study heterogeneity was quantified using Cochran's Q statistic and expressed as the I 2 statistic. Study quality was assessed with the Newcastle–Ottawa Scale. Results Seven studies ( n = 1572) were included in the qualitative synthesis; four were included in the meta‐analysis. Qualitative findings were mixed, with some studies reporting poorer outcomes at higher BMI and others showing no difference. The pooled odds ratio for treatment success in the BMI ≥ 32 kg/m 2 group versus < 32 kg/m 2 was 0.87 (95% CI: 0.68–1.11). Between‐study heterogeneity was low ( Q = 4.11, df = 3, p = 0.25; I 2 = 27%), indicating relatively consistent effect estimates across studies. Conclusion Elevated BMI was associated with a nonsignificant trend toward lower HGNS surgical success, but outcomes were broadly consistent across studies. Many patients with BMI ≥ 32 kg/m 2 achieved meaningful objective and subjective improvements, challenging rigid BMI‐based eligibility criteria and supporting individualized candidacy assessment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".