Transoral Versus Endoscopic Examination in Predicting Outcomes of Hypoglossal Nerve Stimulation for Obstructive Sleep Apnea
Bibliographic record
Abstract
Objectives/Hypothesis To examine the correlation between transoral and awake endoscopic examination and investigate their respective ability to predict outcomes of hypoglossal nerve stimulation (HGNS). Study Design Retrospective cohort study at a US medical center. Methods Subjects were adults with apnea‐hypopnea index (AHI) >15 events/hr who underwent HGNS according to standard indications. Eligible subjects had diagnostic preoperative sleep studies, full‐night efficacy postoperative studies, as well as postoperative video recordings of transoral examination and awake endoscopy. Recordings were independently scored by two blinded reviewers. Cohen's κ coefficient, Student t test, and χ 2 analyses were performed. Results Fifty‐seven patients met all inclusion criteria. On average, patients were Caucasian, middle aged, and overweight. The mean preoperative AHI was 36.7 events/hr, which improved significantly to 18.3 events/hr following HGNS ( P < .01). Overall, the response rate (defined as AHI reduction >50% and AHI < 20 events/hr) was 49%. There was slight correlation between transoral tongue protrusion and endoscopic tongue base movement (κ = 0.10). On transoral examination, patients with minimal/moderate tongue motion achieved a greater mean AHI reduction than patients with full motion (26.0 ± 18.0 vs. 12.8 ± 24.1, P = .02). In contrast, on awake endoscopy, patients with minimal/moderate tongue motion achieved a lesser mean AHI reduction than patients with full motion (8.7 ± 19.9 vs. 22.1 ± 22.7, P = .04). Conclusions Transoral tongue protrusion bears an inverse relationship to HGNS success and correlates poorly with endoscopic tongue base movement. Endoscopic tongue base motion appears reflective of response to HGNS, with greater motion corresponding to greater AHI reduction. Level of Evidence 4 Laryngoscope , 131:675–679, 2021
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 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 | 0.000 | 0.001 |
| 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) | 0.000 | 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".