Characterization of postoperative LASIK ectasia features on higher-order aberration excimer ablation maps
Bibliographic record
Abstract
BACKGROUND: To characterize anterior corneal higher-order aberration (HOA) excimer ablation map patterns in postoperative LASIK ectasia (POE) and to examine correlations between newly identified corneal HOA ablation map features of POE and known topographic indices. METHODS: Prospective multicenter non-interventional descriptive study. A total of 28 eyes from 22 POE patients were enrolled. The postoperative HOA ablation map was derived from Topolyzer Vario corneal imaging at the time of POE diagnosis. Features that recurred were identified and then analyzed. Correlations to Orbscan indices were studied. RESULTS: An arrangement of two elliptical paracentral ablation islands, deep inferior and shallow superior, in direct mirror-like opposition to each other, were identified on all HOA maps. The paracentral islands were accompanied by peripheral ablation crescents. The deep paracentral inferior island 'hot spot' coincided with the topographical apical POE cone and was highly reproducible in angular position (249.3 ± 17.3°). There was significant variation in ablation depth (shallow superior island: 11.5 ± 6.9 μm and deep inferior island: 32.5 ± 18.8 μm). The superior crescents had high variability in depth (34.8 ± 18.9 μm). Strong correlations were found between the corneal irregularity index and the ablation depth difference between the deep and shallow paracentral islands (R = 0.96; P < 0.0001). CONCLUSION: The corneal HOA excimer ablation map revealed a recurring, distinct, easily recognizable pattern in POE eyes. Validated Orbscan POE indices and HOA ablation map islands showed a strong correlation. It is possible to extract useful information from the corneal HOA ablation map, potentially making it suitable for diagnosing and monitoring POE although more studies are needed.
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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 | 0.001 | 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".