Minimal Clinically Important Difference of the Standardized Cosmesis and Health Nasal Outcomes Survey
Bibliographic record
Abstract
BACKGROUND: The minimal clinically important difference (MCID) for the Standardized Cosmesis and Health Nasal Outcomes Survey (SCHNOS) has not been determined. OBJECTIVES: The authors sought to define the MCID for both domains of the SCHNOS questionnaire. METHODS: This prospective cohort study included patients who underwent functional, cosmetic, or combined rhinoplasty operation from June 2017 to June 2018 at a tertiary referral center. The average preoperative, postoperative, and change in scores were calculated for the nasal obstruction symptom evaluation scale (NOSE) and SCHNOS. Anchor-based MCIDs were estimated for both SCHNOS subscales to define change in obstruction and cosmesis perceived after the rhinoplasty. RESULTS: Eighty-seven patients (69% women, 31% males) with a mean age (standard deviation [SD]) of 38 years (14.7) at the time of surgery were included. The mean postoperative follow-up period (SD) was 145 days (117). The mean preoperative score (SD) for the NOSE was 52 (32), SCHNOS for nasal obstruction (SCHNOS-O) score was 55 (33), and SCHNOS for nasal cosmesis (SCHNOS-C) score was 50 (26) points. Postoperatively, the NOSE score was 23 (22), SCHNOS-O score was 24 (23), and SCHNOS-C score was 13 (18) points. The mean change in scores (SD) for NOSE, SCHNOS-O, and SCHNOS-C was -29 (37), -31 (38), and -37 (28), respectively. The calculated MCID for SCHNOS-O was 26 (16) and for SCHNOS-C was 22 (15) points. The MCID for NOSE was 24 (13) points. A sensitivity test for the patients with a follow-up ≥3 months showed only slightly different MCID estimates: 28 (17) for SCHNOS-O, 18 (13) for SCHNOS-C, and 24 (15) points for NOSE. CONCLUSIONS: For the obstruction domain SCHNOS-O, the MCID was 28 points. For the cosmetic domain SCHNOS-C, the MCID was 18 points.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".