A Comparison of Endothelial Cell Loss After Phacoemulsification in Penetrating Keratoplasty Patients and Normal Patients
Bibliographic record
Abstract
PURPOSE: To compare phacoemulsification-related endothelial cell loss in transplanted corneas and normal corneas. METHODS: Forty-nine patients who underwent phacoemulsification/intraocular lens insertion after penetrating keratoplasty (PK-CAT group) (50 eyes) were compared with 65 patients who underwent phacoemulsification/intraocular lens insertion only (CAT group) (100 eyes). The PK-CAT group was divided into corneal endothelial dysfunction (CED) and opacity subgroups according to recipient endothelial function. Effective phacoemulsification time and endothelial density were analyzed. RESULTS: The endothelial cell density after cataract surgery from 1 month (1772.72 +/- 315.89) to 24 months (917.25 +/- 372.75) in the PK-CAT group was significantly lower than that before cataract surgery (2189.36 +/- 358.68) (P < 0.05) but that in CAT group was not significantly different from baseline during follow-up time (P < 0.05). The rate of graft survival in the opacity subgroup (82.0%) of the PK-CAT group was higher than that in the CED subgroup (54.5%) after 2 years (P < 0.05). The mean endothelial density in the opacity subgroup (1216.73 +/- 271.63 cells/mm2) of the PK-CAT group was significantly higher than that in the CED subgroup (632.50 +/- 238.29 cells/mm2) at 2 years after cataract surgery (P < 0.05). CONCLUSIONS: The phacoemulsification-related endothelial cell loss in transplanted corneas was higher than that in normal corneas. A possible factor contributing to higher endothelial cell loss in transplanted corneas is recipient endothelial dysfunction.
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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 | 0.001 | 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".