Intracameral Fibrinous Reaction During Descemet’s Membrane Endothelial Keratoplasty
Bibliographic record
Abstract
Purpose To determine the outcomes and predisposing factors of Descemet’s membrane endothelial keratoplasty (DMEK) complicated by intraoperative fibrinous reaction.Methods Retrospective cohort study of 346 DMEKs. Medical charts were reviewed for recipient demographics, surgical indications, donor characteristics, and potential predisposing ocular and systemic factors. For DMEKs complicated by fibrin, surgeons’ notes on events leading to fibrin formation and on its intraoperative management, occurrence of graft detachment, primary failure, re-bubbling or regrafting, time to graft clearing, and endothelial cell density were additionally collected.Results Fifteen (4.3%) DMEKs were complicated by fibrin, which interfered with and protracted graft unfolding in all cases. Median surgical time was longer than for uncomplicated DMEKs (p = 0.001). Graft positioning at the end of surgery was suboptimal in seven eyes (47%) and failed in three (20%). Re-bubbling, primary failure, and regraft rates were of 40%, 33% and 53%, respectively. The corneas that cleared did so in three to eight weeks, with median endothelial cell loss of 53% at 12 months. Use of anticoagulants was a preoperative risk factor (p = 0.01). Surgeon-identified intraoperative factors included beginner surgeons (87%), prolonged AC shallowing (47%) and graft manipulations (33%), intraocular bleeding (27%), new injector (20%), tight donor scroll (13%), and floppy iris (13%).Conclusion Fibrinous reaction is a rare intraoperative complication of DMEK that interferes with graft unfolding and results in poor outcomes. Anticoagulant use appears to be a risk factor and may be compounded by surgical trauma to vascular tissues and prolonged surgical maneuvers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".