Collagen Crosslinking for Keratoconus Can Change Scleral Shape
Bibliographic record
Abstract
Collagen crosslinking (CXL) for keratoconus is known to decrease, halt or even partially reverse progression of keratoconus. We report on a case where a substantial effect on scleral shape was also demonstrated. This keratoconus patient, who was successfully wearing a scleral lens, underwent collagen crosslinking OS. Three months post crosslinking, the patient was unable to wear his previous scleral lens due to lens discomfort. Elevation mapping pre and post crosslinking, with a new corneal-scleral topography system, showed a decrease in size and change in shape of the cone, as well as a substantial change in the scleral elevation pattern at a 16mm chord diameter. The change in the scleral elevation pattern was best observed on scleral shape plots which graph the sagittal height (SAG) value on the Y-axis vs. meridian on the X-axis. The pre-crosslinking plot resembled a standard toric curve although the depression inferiorly at 330° was deeper than that superiorly by 250µ. The post-crosslinking plot changed substantially with the steep axis superiorly being markedly attenuated: the SAG superiorly (102°) decreased post-crosslinking by >300µ. Attempts to virtually fit the eye surface post-crosslinking with a standard posterior toric haptic demonstrated a good fit superiorly and a poor fit inferiorly. The post-crosslinking scleral toricity plot was used to obtain quantitative information to manufacture a custom design conforming to this specific eye. The resulting lens was comfortable, well centered and resulted in a BCVA of 20/30.
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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 | 0.000 |
| 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".