Reporting Outcomes and Outcome Measures in Open Rhinoplasty: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Comparative studies have shown little statistical difference in outcomes following rhinoplasty, demonstrating near equivalent results across all surgical techniques. Cross-study comparisons of these trials are difficult because variation in outcome reporting prevents statistical pooling and analysis. OBJECTIVES: The authors sought to identify all outcomes and outcome measures used to evaluate postoperative results in rhinoplasty. METHODS: An extensive computerized database search of MEDLINE and EMBASE was performed; all trials involving n ≥ 20 patients, aged 18 years and older undergoing a primary, open rhinoplasty procedure, were included for review. RESULTS: Of the 3235 citations initially screened, 72 studies met the stated inclusion criteria. A total of 53 unique outcomes and 55 postoperative outcome measures were identified. Outcomes were divided into 6 unique domains: objective signs, subjective symptom severity, physical function related to activities of daily living, patient satisfaction, surgeon satisfaction, and quality of life. The identified outcome measures consisted of 5 nasal-specific, author-reported instruments; 5 nasal specific, patient-reported instruments; 5 patient-reported, generic instruments; and 40 author-generated instruments. Of the outcome measures identified, the Rhinoplasty Outcomes Evaluation, Sino-Nasal Outcome Test-22, and FACE-Q were the only instruments to demonstrate adequate validity, reliability, and responsiveness to change in patients who underwent a rhinoplasty procedure. CONCLUSIONS: There is heterogeneity in the outcomes and outcome measures employed to assess postsurgical outcomes following rhinoplasty. A standardized core outcome set is urgently needed to make it possible for future investigators to compare results of various techniques in rhinoplasty surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".