Early Refractive and Clinical Outcomes of High-Myopic Photorefractive Keratectomy as an Alternative to LASIK Surgery in Eyes with High Preoperative Percentage of Tissue Altered
Bibliographic record
Abstract
OBJECTIVE: To analyze the safety and efficacy of high-myopic PRK as an alternative to LASIK surgery in patients with a high preoperative percentage tissue altered (PTA). DESIGN: Retrospective interventional case series. PARTICIPANTS: Charts of 256 consecutive eyes that underwent PRK with application of mitomycin-C 0.02% for high myopia were retrospectively reviewed. METHODS: Refractive (refraction and refractive accuracy) and visual outcomes (uncorrected and corrected visual acuities), as well as occurrence of haze in the eyes with preoperative PTA expected to be higher than 40% with a 110-micron flap if undergoing LASIK surgery, were analyzed. RESULTS: Mean follow-up was 7.3 ± 4.8 months. A total of 187 of 256 eyes (73.0%) were included in the analysis because they were expected to have a PTA greater than 40%, should they have undergone LASIK surgery. The actual mean PTA of those eyes following PRK was 31.8 ± 2.2%, and none had a PTA ≥ 40%. UDVA of 20/16, 20/20, and 20/25 or better was achieved in 1.2% (2 eyes), 65.5% (112 eyes), and 85.4% (146 eyes), respectively. The percentage of eyes with postoperative SE within ±0.5 D and ±1.0 D of planned SE was 71% and 93%, respectively. None of the eyes lost 2 or more lines of CDVA. The rate of stromal haze, managed successfully with topical steroids only, was 4.8%. CONCLUSION: High-myopic PRK with application of mitomycin-C in the eyes at risk of developing ectasia because of high preoperative PTA was demonstrated to be a safe and effective alternative to the LASIK procedure.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".