Outcomes of Descemet Stripping Automated Endothelial Keratoplasty in Patients With Previous Glaucoma Drainage Device Insertion
Bibliographic record
Abstract
PURPOSE: To report the outcomes of Descemet stripping automated endothelial keratoplasty (DSAEK) in patients with a previously inserted glaucoma drainage device (GDD). METHODS: The clinical records of patients who had DSAEK surgery with a history of GDD insertion were reviewed. RESULTS: Eleven eyes of 10 patients (7 men and 3 women) were included. The mean age for DSAEK surgery was 67.2 ± 20.4 years (range, 22-93 years). The mean follow-up after DSAEK surgery was 20.2 ± 10.7 months (range, 3-37 months). Preoperative mean logarithm of the minimum angle of resolution (logMAR)-corrected distance visual acuity was 1.8 ± 0.6 (range, 20/100 to hand motions), and this improved to 0.9 ± 0.8 (range, 20/40 to hand motions) at the final follow-up (P < 0.01). There was no statistical difference in mean pre-DSAEK versus final post-DSAEK intraocular pressure (P = 0.88). Six of 11 eyes (54.5%) had double GDD insertion before DSAEK surgery. GDD tubes were trimmed in 6 eyes (54.5%), and no eyes required further glaucoma surgical intervention after DSAEK surgery. Postoperative complications included early postoperative graft dislocation in 4 eyes (36.4%) that were successfully repositioned. Four eyes (36.4%) had an episode of endothelial rejection, with 2 patients (18.2%) requiring repeat endothelial keratoplasty for endothelial failure. The mean donor endothelial cell count was 2740 cell per square millimeter preoperatively and reduced to 858 cells per square millimeter at the final follow-up, a significant mean reduction of 69%. This was significantly greater than previously reported endothelial cell loss after DSAEK alone at our institution. CONCLUSIONS: Although surgery may be more challenging, the presence of GDD is not a contraindication to DSAEK surgery. In this series, there was a high rate of dislocation that was successfully managed with rebubbling. DSAEK seems to be a reasonable alternative to penetrating keratoplasty for corneal decompensation after GDD.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".