Outcomes of Corneal Transplantation After Minimally Invasive Corneal Neurotization in Children
Bibliographic record
Abstract
PURPOSE: To describe the outcomes of corneal transplantation after minimally invasive corneal neurotization (MICN) in pediatric patients. METHODS: Medical records of all children who underwent corneal transplantation post-MICN with sural nerve graft for neurotrophic keratopathy between 2015 and 2021 were reviewed retrospectively. Data collected included demographic information, ocular comorbidities, maximum corneal sensitivity by Cochet-Bonnet aesthesiometer (CBA) preoperatively and postoperatively measured in the central graft area, graft survival (primary outcome), and rejection. RESULTS: Of 28 eyes which underwent MICN, six underwent corneal transplant surgery (mean age 11.9 ± 4.4 years) 2.4 ± 0.4 years after initial surgery. Mean maximum recorded CBA across all quadrants before corneal transplantation was 53.3 ± 9.4 mm. Reepithelialization was observed in all eyes by postoperative month 2. Mean follow-up was 4.5 ± 2.1 years. Penetrating keratoplasty was performed in 2 cases, and deep anterior keratoplasty in four cases. Graft survival at final follow-up was 83.3%. Mean recorded central CBA after corneal transplantation was 53.8 ± 8.2 mm. No improvement was observed in visual acuity from baseline (1.2 ± 0.4 logMAR) to final postoperative follow-up (1.1 ± 0.4 logMAR; P = 0.68). CONCLUSIONS: Corneal transplantation after corneal neurotization has survival rates >80%. Manual deep anterior keratoplasty can be performed in patients who have not undergone previous penetrating keratoplasty. Despite graft clarity, improvement in best-corrected visual acuity may be limited by amblyopia in this age group.
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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 | 0.000 | 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".