Histopathological Study of Delayed Regraft After Corneal Graft Failure
Bibliographic record
Abstract
PURPOSE: To evaluate the histopathological features of corneal graft failures over time. METHODS: A single-center retrospective analysis was performed on corneal specimens diagnosed as corneal graft failure retrieved from The Henry C. Witelson Ophthalmic Pathology Laboratory and Registry (Montreal, Canada) over a 9-year period. The corneal buttons were divided into 3 different groups according to the time between the diagnosis of corneal graft failure and regraft. Corneal specimens obtained during keratoplasty were subjected to hematoxylin and eosin and periodic acid-Schiff. Five different histopathological findings were evaluated in each specimen. RESULTS: Overall, the most common histopathological finding was endothelial decompensation (97.2%). Subepithelial pannus (38.9%), vessels in the corneal stroma (11.1%), and anterior synechiae (2.8%) were the other present findings. The inflammatory reaction was considered discrete in 83.3% of the cases. The only significant histopathological finding correlated with time was the presence of vessels in the corneal stroma (P = 0.0092). CONCLUSIONS: Corneal neovascularization, represented by the presence of vessels in the corneal stroma, was the only histopathological finding correlated with time. Because it is a known factor of poor prognosis, our findings strongly support that early regraft has higher chances of success.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".