Does Laser-Assisted Uvulopalatoplasty Work? An Objective Analysis Using Pre- and Postoperative Polysomnographic Studies
Bibliographic record
Abstract
INTRODUCTION: Since its introduction in 1990, the procedure of laser-assisted uvulopalatoplasty (LAUP) has become a popular alternative to UP3 and other surgical procedures for sleep-disordered breathing. Laser-assisted uvulopalatoplasty has proved to be a relatively simple and cost-effective alternative; however, after almost a decade of use on thousands of patients and many studies that show subjective benefits, very few patients have been followed objectively. PURPOSE: Our purpose was to study in an objective, prospective manner the effects of LAUP on snoring volume and duration as well as on apnea index, respiratory disturbance index (RDI), and desaturation index. METHODS: Fifty consecutive patients were evaluated for sleep-disordered breathing; 43 patients were included in the study, and all had pre- and post-LAUP polysomnograms. Patients were divided into groups depending on their preoperative RDI. All subjects had a pre-LAUP history and physical examination and an otolaryngologic examination, including fibre-optic endoscopy. All patients had a preoperative polysomnographic evaluation. An in-office LAUP using CO2 laser and local anaesthetic was performed on all patients, and all had post-LAUP polysomnography an average of 9.4 weeks postoperatively at the same sleep centre. RESULTS: Overall, we found a significant improvement in 60% of patients, with the greatest benefit in patients with a preoperative RDI of greater than 40 per hour. Patients with preoperative RDI < 20 were successfully treated in only 25% of cases.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".