Clinical Results of Topography-based Customized Ablations in Highly Aberrated Eyes and Keratoconus/Ectasia With Cross-linking
Bibliographic record
Abstract
PURPOSE: To report results of a series of highly aberrated corneas treated with a topography-guided excimer laser ablation. METHODS: Retrospective, nonrandomized, consecutive series of eyes treated with topography-guided photorefractive keratectomy (TG-PRK) with the customized topographical neutralization technique (TNT). Cases included postoperative refractive surgery decentered ablations, optical zone enlargement, asymmetrical astigmatism, postoperative radial keratotomy (RK), postoperative keratoplasty, keratoconus combined with collagen cross-linking (CXL), and postoperative LASIK ectasia combined with CXL. Uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), and manifest refraction were analyzed preoperatively and 6 months postoperatively. RESULTS: In decentered ablation cases, 94% of 37 eyes were within 1.00 diopter (D) of the attempted refractive outcome, with 76% within 0.50 D. Mean topographic, central, optical zone of uniform (monodioptric) power increased from 3.5 to 5.2 mm in 25 eyes. Thirty-one eyes treated for asymmetrical astigmatism showed improvement in cylinder from mean 1.31 to 0.52 D. Ten of 11 eyes treated for previous RK astigmatism achieved postoperative UDVA 20/40 or better. Twenty-seven eyes with postoperative keratoplasty astigmatism were treated, with 7 (25.9%) eyes gaining > or = 2 lines and 12 (44.4%) eyes gaining > or = 1 line of CDVA. Of eyes with keratoconus that were treated using TG-PRK with CXL, 42 (58%) eyes had UDVA 20/40 or better, and 66 (92%) eyes had CDVA 20/40 or better. Twelve (71%) of 17 eyes treated for postoperative LASIK ectasia using TG-PRK with CXL had UDVA 20/40 or better. Nine (53%) eyes gained > or = 2 lines of CDVA. CONCLUSIONS: Topography-guided laser treatment with custom TNT, combined with CXL in keratoconus and ectasia, is an effective, safe, and increasingly predictable option for highly aberrated corneas.
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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 | 0.001 |
| 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".