Upper airway stimulation therapy and sleep architecture in patients with obstructive sleep apnea
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To quantify changes in sleep architecture before and after upper airway stimulation (UAS) therapy in patients with obstructive sleep apnea. STUDY DESIGN: Retrospective chart review. METHODS: This study was performed at a single-institution tertiary academic care center. Patients who responded successfully to UAS implantation were selected for this study. Preoperative and postoperative sleep studies were compared to determine sleep architecture changes. Primary outcomes included sleep architecture parameters such as N1, N2, N3, and rapid eye movement (REM) in addition to others. Secondary outcomes included body mass index. RESULTS: Thirty-five patients met inclusion criteria for this study. There was significant improvement across several sleep architecture parameters. N1 sleep percent decreased from 16.7% ± 2.1% preoperatively to 10.1% ± 1.6% postoperatively (P = .023). Time spent in N2 increased from 148.0 ± 12.4 minutes to 185.5 ± 10.4 minutes (P = .030), whereas N3 increased from 21.9 ± 5.0 minutes to 57.0 ± 11.1 minutes (P = .013). No significant changes were observed in REM sleep. Arousal index decreased from 38.8 ± 4.0 to 30.3 ± 4.0 (P = .050). CONCLUSIONS: There was significant improvement across several sleep architecture parameters among patients who responded successfully to UAS implantation. LEVEL OF EVIDENCE: 4 Laryngoscope, 130:1085-1089, 2020.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".