Clinical outcomes of Descemet membrane endothelial keratoplasty performed in eyes with keratoconus and corneal endothelial dysfunction
Bibliographic record
Abstract
PURPOSE: To evaluate the clinical outcome of Descemet membrane endothelial keratoplasty (DMEK) performed in eyes with comorbid keratoconus (KCN) and corneal endothelial dysfunction. METHODS: Twenty-five consecutive eyes of 14 patients with comorbid stable KCN underwent DMEK for corneal endothelial dysfunction; best spectacle corrected visual acuity (BSCVA), maximum corneal curvature (Kmax), maximum corneal power (Pmax), central corneal thickness (CCT), and intra- and postoperative complications were assessed. RESULTS: Excluding eyes requiring re-transplantation for primary graft failure (n = 3), all eyes showed improvement in BSCVA, reaching ≥ 20/40 (0.5) in 86%, ≥ 20/25 (0.8) in 55%, and ≥ 20/20 (1.0) in 27% by one month postoperatively; 90%, 76%, and 48% by 6 months postoperatively; and 88%, 76%, and 47% by 12 months postoperatively. CCT decreased from 571μm preoperatively to 485μm at 1 month (p < 0.001) and 481μm at 12 months (p < 0.001). Kmax decreased by a median of 1.4 diopters (D) at 1 month (p = 0.003) and 3.1 D at 12 months (p = 0.021), and every eye with a preoperative Kmax ≥ 46 D demonstrated flattening. Pmax decreased by 2.1 D at 1 month (p = 0.001) and 4.0 D at 12 months (p = 0.016). CONCLUSION: DMEK is technically feasible in eyes with comorbid KCN and may give excellent outcomes visual and refractive outcomes, including significant corneal flattening, which may potentially create a visually significant hyperopic shift in patients with severely ectatic corneas.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".