Profilometry-Guided Scleral Lenses Improve Visual Acuity and Reduce Ocular Aberrations in Irregular Corneas: A Retrospective Case Series
Bibliographic record
Abstract
OBJECTIVES: Scleral lenses (SLs) represent a key treatment for visual rehabilitation in patients with irregular corneas, such as keratoconus (KC), pellucid marginal degeneration (PMD), and postlaser in situ keratomileusis (LASIK) ectasia. This study evaluates the impact of profilometry-guided SLs on visual acuity (VA) and ocular aberrations in these patients. METHODS: Medical records of 23 eyes from 23 patients with KC, PMD, and post-LASIK ectasia were reviewed. All patients were fitted with profilometry-guided SLs. High-contrast visual acuity (HCVA), low-contrast visual acuity (LCVA), and aberrometry parameters (Strehl ratio, higher-order root mean square (HO-RMS), coma, spherical aberration, and trefoil) were analyzed before and during SL wear. RESULTS: HCVA improved significantly from 0.62±0.09 logMAR at baseline to 0.03±0.01 logMAR with SL wear ( P <0.05). LCVA also showed significant improvements ( P <0.05). HO-RMS decreased from 2.70±0.54 D to 1.00±0.20 D ( P <0.05), with notable reductions in coma (1.31±0.21 D to 0.49±0.04 D) and trefoil (1.26±0.29 D to 0.34±0.09 D). CONCLUSIONS: Profilometry-guided SLs significantly improve VA and reduce higher-order aberrations in patients with irregular corneas, offering an effective nonsurgical solution for enhancing vision quality in these complex cases.
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How this classification was reachedexpand
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 | 0.005 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".