The Role of Postoperative Bandage Contact Lens in Patients Undergoing Fasanella-Servat Ptosis Repair
Bibliographic record
Abstract
PURPOSE: To determine whether a bandage contact lens (BCL) improves patient comfort in the postoperative period in patients undergoing ptosis repair using the Fasanella-Servat technique, compared with no BCL. METHODS: In this prospective, randomized, double-masked, comparison study, all patients had bilateral Fasanella-Servat surgery. A total of 30 patients were randomized to receive a BCL in one eye and no BCL in the other eye. Patient discomfort was measured as the primary outcome using the Eye Sensation Scale. Blurred vision was measured as a secondary outcome using selected questions from the Ocular Surface Disease Index. The surgeries were performed by 2 surgeons (J.T.H and R.S.A). Outcomes were measured one week following the procedure. RESULTS: Patients reported significantly less discomfort in the eye receiving a BCL, with only 13.3% ranking discomfort as "moderate" or "severe," compared with the eye not receiving BCL, where 63.3% of patients rated discomfort as "moderate" or "severe" (p < 0.001). There was no significant difference in patient-reported blurred vision between the 2 groups (p = 0.520). CONCLUSIONS: The use of a bandage contact lens after Fasanella-Servat procedure for ptosis repair is recommended as it improves patient comfort. In addition, it has no detrimental effect on patient-reported blurring of vision.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".