Deep Anterior Lamellar Keratoplasty for Post-LASIK Ectasia
Bibliographic record
Abstract
PURPOSE: To describe 2 cases of post-laser in situ keratomileusis (LASIK) ectasia managed with deep anterior lamellar keratoplasty (DALK). METHODS: Clinical findings, surgical interventions, and outcomes are reported. The surgical technique of DALK is described. RESULTS: Two patients developed progressive loss of vision after LASIK surgery with enhancement procedure(s). Corneal ectasia was diagnosed on the basis of clinical findings, progressive central corneal thinning on pachymetry, and topographical changes with irregular astigmatism and inferior corneal steepening. Both patients underwent uneventful DALK surgery, in which the anterior 80% of the central corneal stroma was replaced by a donor button and sutured in place. The postoperative recovery was uneventful, except for mild interface haze in 1 case, which resolved within 2 weeks of surgery. However, 1 patient underwent additional surgery, including clear lens extraction with intraocular lens placement, astigmatic keratotomies, and photorefractive keratectomy (PRK) to achieve good unaided visual acuity. At last follow-up, at least 2 years after DALK, both patients were satisfied with their vision. Their uncorrected visual acuity (UCVA) was 20/60+ and 20/40- in their operated eyes, improving to 20/40+ and 20/30- with minimal refractive corrections. The grafts and lamellar interfaces were clear. CONCLUSIONS: We believe that DALK should be considered as an alternative to penetrating keratoplasty for the surgical management of post-LASIK ectasia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".