Photorefractive Keratectomy With 0.02% Mitomycin C for Treatment of Residual Refractive Errors After LASIK
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: To evaluate the efficacy and safety of prophylactic mitomycin C (MMC) during photorefractive keratectomy (PRK) over LASIK flaps for the treatment of residual refractive errors following LASIK. METHODS: In this single center, retrospective clinical study, 30 eyes of 33 patients (mean age 37.2 years) who had MMC (0.02%, 30 to 120 seconds) during PRK for the treatment of residual refractive errors following myopic LASIK were evaluated. The retreatment procedures were performed with a VISX S4 laser with iris registration. All patients underwent slit-lamp microscopy, manifest and cycloplegic refraction, corneal topography, pachymetry, pupillometry, and wavefront analysis pre- and postoperatively. All patients underwent follow-up at 1 day, 1 week, and 1, 3, and 6 months and thereafter as required. RESULTS: Mean time between LASIK and PRK retreatment was 67.3 months (range: 7 to 113 months). No intra- or postoperative complications occurred during primary LASIK or PRK retreatment. Mean spherical equivalent refraction of attempted correction with PRK was -0.94 diopters (D) (range: -2.38 to +0.75 D). At mean 7.1-month follow-up, the average uncorrected visual acuity (UCVA) improved from 20/50 (range: 20/30 to 20/200) to 20/28 (range: 20/15 to 20/70). Twenty-seven of 30 eyes showed improvement in UCVA. Two eyes had subjective improvement of glare symptoms (and objective improvement in higher order aberrations), and one eye lost one line of best spectacle-corrected visual acuity due to unrelated corneal abrasion in the postoperative period. None of the eyes in the cohort developed postoperative haze. CONCLUSIONS: Photorefractive keratectomy with prophylactic MMC (0.02%) is a safe and effective option for treating myopic regression following LASIK. A single intraoperative application of 0.02% MMC for as few as 30 seconds was effective in preventing postoperative haze formation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 it