Preoperative refraction, age and optical zone as predictors of optical and visual quality after advanced surface ablation in patients with high myopia: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: To investigate the factors associated with optical and visual quality of advanced surface ablation in high myopia. DESIGN: A cross-sectional study of high myopic eyes treated with laser epithelial keratomileusis (LASEK)/epipolis laser in situ keratomileusis (Epi-LASIK). SETTING6: Eye and ENT Hospital of Fudan University in Shanghai. METHODS: One hundred and thirty-eight high myopic eyes (138 patients) (myopia -6 D or more) were examined more than 12 months after LASEK or Epi-LASIK with advanced surface ablation on the MEL 80 excimer laser (Zeiss AG, Jena, Germany). Refraction, higher order aberrations (HOAs) and contrast sensitivity before and after surgery were evaluated. Factors including preoperative refraction, age, gender, central corneal thickness, pupil size, optical diameter, ablation depth and flap creation method were analysed for association with postoperative high-order aberration, contrast and glare sensitivities, and different analytic diameters. RESULTS: HOAs increased significantly postoperatively (p<0.05), with the most significant change found in Z(spherical aberration). At a 5 mm analysis diameter, increased coma was associated with age; increased spherical aberration difference was associated with age, optical zone diameter and method of epithelial flap creation. At a 3 mm analysis diameter, none of the factors contributed to changes in HOAs. Higher preoperative refractive error was associated with decreased contrast and glare sensitivity at each spatial frequency. CONCLUSION: A larger optical zone diameter design is recommended to achieve better visual quality in advanced surface ablation for high myopia correction. Age and preoperative refraction may help predict postoperative visual quality.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".