Wait times for endoscopic sinus surgery influence patient‐reported outcome measures in patients with chronic rhinosinusitis who fulfill appropriateness criteria
Bibliographic record
Abstract
BACKGROUND: Previous studies on the impact of wait times for endoscopic sinus surgery (ESS) in medically recalcitrant chronic rhinosinusitis (rCRS) have not examined its influence on the 5 distinct symptoms domains of the 22-item Sino-Nasal Outcome Test (SNOT-22), and have not applied evidence-based surgical indications. Our primary study objective was to investigate the impact of ESS wait times on postoperative SNOT-22 global and symptom domain scores in patients with rCRS deemed "appropriate" surgical candidates. METHODS: This was a retrospective analysis of adult patients with rCRS undergoing ESS, categorized as "appropriate" surgical candidates. Primary outcome measure was change in SNOT-22 global/symptom domain score (preoperative - 6-month postoperative). Correlational analyses were performed between wait time and change in SNOT-22 global and symptom domain scores. For significant negative correlations, the threshold wait time to generate a worsening in health-related quality-of-life (HRQoL) equivalent to the mean clinically important difference (MCID) was calculated. RESULTS: A total of 104 patients with a mean ± standard deviation (SD) wait time of 310.8 ± 155.9 days were analyzed. Postoperative SNOT-22 global and symptom domain scores significantly improved postoperatively. Wait time for ESS was negatively correlated with change in SNOT-22 global, rhinologic, extranasal rhinologic, and ear/facial domain scores (p < 0.05), and a wait time threshold of 287, 452, 421, and 381 days corresponded to a decrease equivalent to the MCID, respectively. CONCLUSION: We identified less improvement in HRQoL after ESS with increasing surgical wait time. Moreover, prolonged wait times may result in less improvement in disease-specific symptoms, but do not appear to worsen psychological or sleep dysfunction.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".