Peripheral Endothelial Cell Damage After Trephination of Donor Tissue
Bibliographic record
Abstract
PURPOSE: To evaluate and quantify the degree and pattern of donor endothelial cell damage, which occurs with mechanical trephination of donor corneal tissue. METHOD: Twenty donor corneal-scleral tissues were used for these paired experiments. The tissues were randomized for trephination with 10 tissues trephinated by an 8.0-mm-diameter Barron trephine (Katena, Denville, NJ), and 10 tissues trephinated with an 8.0-mm-diameter UltraFit Coronet trephine (distributed by Angiotech, British Columbia, Canada) by the same investigator. Trephinated corneal buttons were then stained with vital dye stain, and the endothelial layer image captured with digital photography. The images were then analyzed by digital planimetry, and the pattern and quantity of endothelial damage was determined by an investigator who was masked to the specific trephine used for the individual tissue. RESULTS: Trephination created a pattern of circular damage at the edge of the donor button in every case with no break in continuity of the circle, but some portions of the circle were wider than others. Occasional, scattered, peripheral small areas also displayed damage, but no significant striae, stretch, or other central damage was noted in any donor. The mean percent damage in the series was 6.35% +/- 0.90% (range: 4.33%-7.78%). The UltraFit Coronet trephinations averaged damage of 5.64% +/- 0.85% (range: 4.33%-6.69%), and the Barron trephinations averaged damage of 6.50% +/- 0.95% (range: 4.92%-7.78%). Although 8 of 10 experimental pairs of trephinations demonstrated less peripheral endothelial damage with the UltraFit Coronet trephine, the mean damage between each group did not reach statistical significance in this small series. (P = 0.08) CONCLUSIONS: Donor mechanical trephination of full-thickness corneal tissue creates relatively consistent amounts of peripheral edge damage and likely no central endothelial damage. There may exist differences in edge damage between different mechanical trephination systems, and a direct comparison to laser-created trephination is needed.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".