Intersurgeon Variability in Proptosis Reduction After Orbital Decompression for Thyroid Eye Disease: A Multicenter Analysis
Bibliographic record
Abstract
PURPOSE: This study assesses intersurgeon variability in proptosis reduction after orbital decompression for thyroid eye disease. METHODS: This multicenter retrospective study included patients with thyroid eye disease who underwent orbital decompression from 1 of 7 surgeons at 7 different institutions between January 2002 and December 2018. Data were included if a single decompression technique was performed on ≥10 patients by ≥2 surgeons. The primary outcome was postoperative change in proptosis with emphasis on comparison among surgeons utilizing similar surgical techniques. Statistical analysis was performed with χ 2 and ANOVA testing, and a multivariable logistic regression model was generated. RESULTS: Six hundred thirty-three orbits that underwent orbital decompression were included. Five different decompression techniques were analyzed: medial wall (n = 29), fat + lateral wall (n = 113), medial wall + floor (n = 123), fat + lateral wall + medial wall (n = 140), and fat + lateral wall + medial wall + floor (n = 228), without significant difference in proptosis reduction among surgeons. Surgeons did not demonstrate significant differences in outcomes at different time points compared with each other or themselves. Outcomes when comparing endoscopic versus open medial wall decompression varied among surgery types. Multivariate modeling revealed a statistically significant association between postoperative change in proptosis with preoperative proptosis ( p < 0.001). CONCLUSIONS: Postoperative change in proptosis did not differ significantly between surgeons utilizing similar orbital decompression techniques for patients with thyroid eye disease. This study may strengthen the statistical validity of multicenter clinical trials assessing orbital decompression outcomes performed by surgeons employing uniform surgical techniques, thereby advancing our understanding of optimal surgical management strategies for thyroid eye disease.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".