Riboflavin/Ultraviolet A Corneal Collagen Cross-linking for the Treatment of Keratoconus: Visual Outcomes and Scheimpflug Analysis
Bibliographic record
Abstract
PURPOSE: To evaluate the safety and efficacy of corneal collagen cross-linking (CXL) by riboflavin/UV light for the treatment of keratoconus. METHODS: This randomized, prospective, and comparative study involved 10 eyes with keratoconus diagnosed between September 2006 and January 2008. Each patient underwent CXL in the keratoconus eye. Preoperative and postoperative (at 1, 3, 6, and 12 months) biomicroscopy examinations, distance uncorrected and best-corrected visual acuities, refractive error, endothelial cell counts, keratometry readings, ultrasound pachymetry, macular thickness, and Scheimpflug analyses were performed and compared. RESULTS: Mean uncorrected visual acuity was 1.18 logarithm of the minimum angle of resolution preoperatively and 0.46 logarithm of the minimum angle of resolution at 12 months postoperatively (P < 0.001). Statistically significant reductions in the mean maximum [2.66 diopter (D), P = 0.04] and minimum (1.61 D, P = 0.03) keratometry values were present at 12 months postoperatively, in addition there was a 2.25 D reduction in the mean spherical equivalent (P = 0.01). At the end of follow-up, 8 (80%) and 6 (60%) of the 10 eyes showed a decrease in the anterior and posterior elevation values, respectively, and the thinnest point of the cornea was statistically thinner by a mean of 13.4 μm (P = 0.03). No statistically significant differences were found between preoperative and postoperative endothelial cell counts and macular thicknesses. The improvements in visual acuity, keratometry readings, and spherical equivalent values occurred progressively during follow-up. CONCLUSIONS: CXL procedure is a safe treatment for keratoconus, yields good visual results, and reduces the progression of the disease, but long follow-up is necessary.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".