Mid-peripheral corneal steepening after orthokeratology
Bibliographic record
Abstract
Purpose: The purpose of this study was to retrospectively examine data from patients who had undergone orthokeratology (OK) to quantify the amount of mid-perpheral steeping in tangential curvature (MP-TC) and total refractive power (TRP) changes. Methods: Charts were reviewed from participants and data from the Pentacam instrument were collected prior to OK and after the final visit. Variables included central flattening (C-TC), the e-value, the mid-peripheral tangential curvatures (MP-TC), total corneal refractive power (TRP), the initial Rx (sphere) and initial corneal curvature (flat K). The group was further subdivided into high and low myopia for comparison. All participants were fitted with the Paragon CRT lenses. Data analysis was conducted to analyse the effects of lenses on TC and TRP. Results: A total of 40 patients (80 eyes) age13.95±6.80, 34 M and 46 F, were successfully fitted with CRT lenses. The average sphere was -4.23±0.90D for Group 1 and -1.89±0.62D for Group 2 The changes in TC and TRP from baseline were significant (both P<0.0001). The difference between the amount of C-TC and the maximum area of MPTC was ≈4.00D in the horizontal meridian and ≈3.00 in the veritcal meridian. The amount of MP-TC change from baseline was ≈2.00D in both meridians. There was a similar change in TRP: the distance from the centre to mid-periphery ≈2.50D. For C-TC, C-TRP, MP-TC, MP-TRP there was no significant difference between the 2 groups, overall (P=0.541 (TC) and P=0.321(TRP)). Conclusion: Results from this study should provide valuable insights into the topographic and refractive changes occurring with orthokeratology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".