Use of a Single Radial Incision to Improve Curvature Matching and Graft Adhesion in Descemet Membrane Endothelial Keratoplasty in a Patient With Keratoconus
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to report a novel surgical technique for altering donor Descemet membrane endothelial keratoplasty (DMEK) curvature to match host posterior stroma in a patient with advanced keratoconus (KC) and endothelial decompensation. METHODS: We report a 56-year-old man with Fuch endothelial dystrophy and KC, who underwent DMEK due to endothelial decompensation. A triangular area of graft detachment centered on the apex of cones persisted after repeat gas tamponade. A radial incision from the graft edge to the apex was used to allow overlapping of the graft, thereby increasing the grafts curvature. RESULTS: The use of a radial incision in the Descemet membrane (DM) graft was made to allow the graft overlap and adapt to the new shape. By matching the donor curvature to that of the hosts posterior curvature, full adhesion of the graft was achieved with the use of a short-acting air bubble by 1 week after the procedure. CONCLUSIONS: The mismatch in the curvature of the DM graft and the host posterior corneal surface, in cases with KC or very steep corneas, should be taken into consideration because it can lead to redundancy folds. These can result in atypical, conical detachments, distinct from the typical peripheral detachments seem commonly in DMEK. A single radial incision in the DM graft combined with air tamponade is a feasible treatment option in cases where DMEK fails to attach because of apparent curvature mismatch between the donor and host.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".