Combined Phototherapeutic Keratectomy, Intracorneal Ring Segment Implantation, and Corneal Collagen Cross-Linking in Keratoconus Management
Bibliographic record
Abstract
PURPOSE: To evaluate the efficacy, predictability, and safety of combined corneal collagen cross-linking (CXL), intracorneal ring segment (ICRS) implantation, and superficial phototherapeutic keratectomy (PTK) in patients with keratoconus. METHODS: Fifty-five eyes received ICRS implantation, followed by CXL and PTK combination treatment. Patients were followed up for 6 months. Primary outcomes included Logarithm of the Minimum Angle of Resolution (LogMAR) uncorrected distance VA (UDVA) and corrected distance VA (CDVA), sphere, cylinder, mean spherical equivalent, index of surface variance, index of vertical asymmetry, keratoconus index, central keratoconus index, index of height asymmetry, and index of height decentration. Secondary outcomes were higher-order aberrations (HOAs), including HOA total, coma, spherical, secondary astigmatism, and trefoil. RESULTS: At 6 months, there was a statistically significant improvement in UDVA, CDVA, sphere, and cylinder compared with baseline (P < 0.001). UDVA improved in 14% of the eyes to 20/25 and 96% had at least 20/40 or better spectacle corrected vision; 30.9% of the eyes were within ±0.5 diopter (D), 45.5% of the eyes were within ±1.0 D, and 74.5% of the eyes were within ±2.0 D. For CDVA, 1 eye (2%) lost 3 lines (but gained UDVA), 11% lost 1 line, 38% showed no change, and 49% gained between 1 and 8 lines of vision. Eighty-eight United Arab Emiratespercent of the eyes had at least 1 line of UDVA visual improvement, 79% improved by ≥2 lines, and 69% improved by ≥3 lines. HOA total, coma, spherical aberration, and secondary astigmatism showed improvements of -0.87 (P < 0.001), -0.84 (P < 0.001), -0.10 (P = 0.002), and -0.15 (P = 0.035), respectively. CONCLUSIONS: A combined procedure of ICRS implantation, CXL, and PTK is effective, predictable, and apparently safe for patients diagnosed with moderate keratoconus.
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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) | 0.000 | 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) | 0.001 | 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".