Endoscopic vidian neurectomy: a prospective case series
Bibliographic record
Abstract
BACKGROUND: Chronic refractory vasomotor rhinitis (VMR) is a debilitating condition that causes significant impairment of quality of life. The purpose of this study is to investigate the efficacy and potential side effects of endoscopic vidian neurectomy as treatment for patients with VMR. METHODS: This study was a prospective, intent-to-follow case series. Inclusion criteria were as follows: (1) patients with debilitating VMR refractory to medical therapy and with significant impact on quality of life; (2) negative allergy history and skin testing; and (3) negative computed tomography (CT) scan to rule out skull-base defect or cerebrospinal fluid (CSF) fistula. Patients underwent bilateral vidian neurectomy via a pterygomaxillary approach. Prior to surgery all patients underwent formal ophthalmologic testing to quantify preoperative ocular and lacrimal function. Ophthalmologic testing was repeated postoperatively at approximately 3 months. Patients also completed surveys regarding rhinologic outcomes including the Sinusitis Symptom Questionnaire (SSQ) and the 22-item Sino-Nasal Outcome Test (SNOT-22) at the following time points: preoperatively, and 1 week, 4 weeks, 12 weeks, 6 months, 1 year, and 2 years postsurgery. Descriptive statistics and analysis of variance (ANOVA) were undertaken. RESULTS: Eleven patients (22 sides) underwent bilateral vidian neurectomy with pathologic confirmation of nerve section in all cases. Average follow-up was 19.4 months. Statistically and clinically significant improvement was measured for both the SSQ and the SNOT-22 and compared with the patients' baseline scores (p < 0.0001). Subscores for rhinorrhea and nasal congestions were also statistically significantly improved (p < 0.05). No incidence of permanent or measureable dry eye has been reported. CONCLUSION: The data suggests that vidian neurectomy is an effective, safe, and definitive treatment for most patients with VMR refractory to medical treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".