In Vivo Confocal Microscopy Reveals Corneal Reinnervation After Treatment of Neurotrophic Keratopathy With Corneal Neurotization
Bibliographic record
Abstract
PURPOSE: To document the presence and location of new sensory nerve fibers after corneal neurotization using in vivo confocal microscopy (IVCM) in 2 patients with neurotrophic keratopathy (NK). METHODS: Two patients with unilateral advanced NK received corneal neurotization to surgically reinnervate the cornea. IVCM was used to identify subbasal nerve fibers and document corneal reinnervation. In 1 patient (case 1), IVCM was performed before and after corneal neurotization; in the second patient (case 2), IVCM was performed after neurotization and corneal transplantation. RESULTS: In case 1, who had hand motion visual acuity due to NK-associated corneal perforation that necessitated cyanoacrylate gluing, preoperative IVCM identified no subbasal nerves; however, subbasal nerves were identified 6 months after corneal neurotization, and there were no further episodes of persistent epithelial defects. In case 2, in whom NK with a total absence of corneal sensation was the result of treated basal skull meningioma, corneal sensation, visual acuity, and ocular surface health improved after corneal neurotization. Deep anterior lamellar keratoplasty was performed 2.5 years after corneal sensation was reestablished. IVCM demonstrated corneal reinnervation at the stromal and subbasal level in a pattern different from the normal cornea. CONCLUSIONS: Corneal neurotization restores corneal sensation by reinnervating the stromal and subbasal layers of the cornea. In doing so, corneal neurotization may halt the process of NK and prevent further visual loss.
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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 | 0.000 |
| 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) | 0.001 | 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".