<scp>P</scp>ang‐<scp>R</scp>otenberg sign—snoring surgery prognosticator: A prospective clinical trial of 153 patients
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To illustrate the reliability of the Pang-Rotenberg (PR) sign as a prognosticator of snoring surgery. Our hypothesis was that patients who are PR-positive have better snoring reduction scores and outcomes than PR-negative patients after nose and palate surgery. STUDY DESIGN: A multicenter prospective series of 153 patients with snoring. METHODS: All patients graded the snoring intensity on a visual analog scale (VAS). All 137 patients enrolled had both the nose surgery and palate surgery. The control group consisted of 16 patients who underwent nasal surgery alone. RESULTS: There were 122 men and 15 women, the mean age was 44.6 years old, and mean body mass index was 26.1. There were 15 simple snorers and 122 obstructive sleep apnea patients. Patients who were PR-positive showed significantly better postoperative snoring VAS reduction (from 9.04 to 1.02) compared to those patients who were PR-negative (from 8.91 to 3.14) (P < .001). The mean follow-up time was 7.4 months. The control group had poor snoring VAS reduction from 9.21 to 6.72. After adjusting for covariates that influence the snoring VAS change due to surgery, we found that PR-negative patients achieved an average of 5.78 improvement in snoring VAS, whereas PR-positive patients achieved an average of 8.02 improvement in snoring VAS (P < .001). CONCLUSIONS: The PR sign is a reliable prognosticator of snoring reduction, after combined nose and palate surgery, for patients with troublesome snoring.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".