Does Adjunctive Under-flap CXL Reduce Regression for Hyperopic LASIK?
Bibliographic record
Abstract
Purpose: To investigate whether adding accelerated under-flap corneal cross-linking to hyperopic laser in situ keratomileusis (LASIK-ufCXL) affects postoperative stability and regression, visual and refractive outcomes, and subjective quality of vision. Methods: This prospective comparative contralateral eye study included 51 patients with hyperopia (102 eyes) who received LASIK-ufCXL in the eye with highest defocus equivalent (DEQ) or randomized when DEQ equal, with the contralateral control eye receiving LASIK alone. After excimer ablation, 0.25% riboflavin was instilled on the stromal bed for 3 minutes. The flap was repositioned, followed by a total irradiation dose of 3.24 J ultraviolet A (UV-A) light administered to the corneal surface, using 18 mW/cm 2 UV-A for 3 minutes. Postoperative hyperopic regression (stability) was the primary outcome measure, defined by the difference in spherical equivalent (SEQ) at 1 week and 24 months postoperatively. Secondary measures reported uncorrected distance visual acuity, corrected distance visual acuity, cylinder vector analysis, subjective quality of vision, subjective night vision disturbances, and corneal haze. Results: At 24 months, the SEQ stability ( P = .4273) and the magnitude of hyperopic regression ( P = .5613) did not significantly differ between groups, with a small trend showing hyperopic regression of 0.50 diopters or greater being less frequent in LASIK-ufCXL eyes. There were no significant differences in accuracy, efficacy, and safety ( P > .05), with a small trend of more residual refractive astigmatism in the LASIK-ufCXL group ( P = .3216, Cohen's d : −0.29). Subjective quality of vision trended inferior in LASIK-ufCXL eyes ( P = .2237, Cohen's d : −0.25), with a greater haze grading ( P = .0466, Cohen's d : 0.41). Conclusions: Postoperative regression and stability were statistically equivalent between hyperopic LASIK vs LASIK-ufCXL, with identical safety. There were small clinical trends of lower efficacy, accuracy, and subjective quality of vision in LASIK-ufCXL eyes. [ J Refract Surg . 2022;38(12):770–779.]
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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) | 0.001 | 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".