Müller Muscle Conjunctival Resection: A Prospective Multicenter Comparison of Eyelid Height at the Immediate, 1-Week, and 3-Month Postoperative Time Points
Bibliographic record
Abstract
PURPOSE: The primary objective was to document change in postoperative marginal reflex distance-1 (MRD1) after Müller muscle conjunctival resection surgery. The secondary objective was to identify predictors of change in postoperative MRD1. METHODS: A multicenter prospective cohort study was performed on patients consecutively recruited for Müller muscle conjunctival resection. MRD1 was measured immediately after Müller muscle conjunctival resection, at the 1-week postoperative visit, and the ≥3-month postoperative visit. MRD1 at the immediate and 1-week time points were compared with MRD1 ≥3 months using descriptive statistics. Predictors of change in MRD1 were analyzed using multivariate regression analysis. RESULTS: A total of 150 patients (226 eyelids) were included. Regarding the immediate to ≥3-month interval, 53.8% of eyelids remained clinically similar (rise or fall ≤0.5 mm), 19.8% rose ≥1 mm, and 26.4% fell ≥1 mm. Regarding the 1-week to ≥3-month interval, 76.5% remained clinically similar, 17.3% rose ≥1 mm, and 6.2% fell ≥1 mm. No variable predicted change in MRD1 over either interval with both clinical and statistical significance. CONCLUSIONS: Immediate postoperative MRD1 is likely to reflect the late result in only 54% of cases. However, 1-week postoperative MRD1 is similar to the late result in 77% of cases and is highly unlikely (6%) to fall by the final visit. No variable significantly impacts change in postoperative MRD1.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".