Patient‐centered decision making in the treatment of chronic rhinosinusitis
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To explore possible factors that might impact a patient's choice to pursue endoscopic sinus surgery (ESS) or continue with medical management for treatment of refractory chronic rhinosinusitis (CRS). STUDY DESIGN: Cross-sectional evaluation of a multicenter prospective cohort. METHODS: Two hundred forty-two subjects with CRS were prospectively enrolled within four academic tertiary care centers across North America with ongoing symptoms despite prior medical treatment. Subjects either self-selected continued medical management (n = 62) or ESS (n = 180) for treatment of sinonasal symptoms. Differences in demographics, comorbid conditions, and clinical measures of disease severity between subject groups were compared. Validated metrics of social support, personality, risk aversion, and physician-patient relationships were compared using bivariate analyses, predicted probabilities, and receiver operating characteristic curves at the 0.05 alpha level. RESULTS: No significant differences were found between treatment groups for any demographic characteristic, clinical cofactor, or measure of social support, personality, or the physician-patient relationship. Subjects electing to pursue sinus surgery did report significantly worse average quality-of-life (QOL) scores on the 22-item Sinonasal Outcome Test (SNOT-22; P < .001) compared to those electing continued medical therapy (54.6 ± 18.9 vs. 39.4 ± 17.7), regardless of surgical history or polyp status. SNOT-22 score significantly predicted treatment selection (odds ratio, 1.046; 95% confidence interval, 1.028-1.065; P < .001) and was found to accurately discriminate between subjects choosing endoscopic sinus surgery and those electing medical management 72% of the time. CONCLUSIONS: Worse patient-reported disease severity, as measured by the SNOT-22, was significantly associated with the treatment choice for CRS. Strong consideration should be given for incorporating CRS-specific QOL measures into routine clinical practice. LEVEL OF EVIDENCE: 2b.
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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 | 0.003 | 0.016 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".