Topical Ganciclovir for Prophylaxis of Cytomegalovirus Endotheliitis in Endothelial Keratoplasty
Bibliographic record
Abstract
PURPOSE: To describe the presentation and management of 2 cases of Descemet stripping automated endothelial keratoplasty (DSAEK) with failure secondary to cytomegalovirus (CMV) infection and prophylaxis with topical ganciclovir to prevent repeat failure of Descemet membrane endothelial keratoplasty (DMEK) regrafts. METHODS: A retrospective chart review was conducted for 2 patients with DSAEK failure secondary to CMV infection. RESULTS: A 70-year-old immunocompetent man (case 1) and a 53-year-old immunocompromised man (case 2) received DSAEK for presumed pseudophakic bullous keratopathy and endothelial decompensation secondary to recurrent uveitis, respectively. Case 1 had first graft failure at 10 months and case 2 at 21 months with inferior edema and keratic precipitates. Both failed to respond to topical steroid drops, and case 1 had 3 subsequent failed DSAEKs. Anterior chamber paracentesis confirmed CMV DNA. Neither had a clinical response to 6 weeks of oral valganciclovir. They were then administered topical ganciclovir (0.15% ophthalmic gel), and repeat endothelial transplant (DMEK) was performed for both patients. They were again administered topical ganciclovir 4 times daily after surgery because aqueous samples remained positive for CMV. Both remain free of inflammation or failure on topical ganciclovir for 21 months (case 1) and 29 months (case 2) with uncorrected visual acuities of 20/40 and 20/25, respectively. CONCLUSIONS: Long-term topical ganciclovir use can prevent recurrence of CMV-associated graft failure even in immunocompromised hosts without side effects of systemic antivirals. DMEK may have advantages over DSEK in eyes with previous CMV infection and in eyes prone to inflammation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".