Four-Year Survival Comparison of Endothelial Keratoplasty Techniques in Patients With Previous Glaucoma Surgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To compare 4-year survival outcomes of Descemet membrane endothelial keratoplasty (DMEK) and Descemet-stripping automated endothelial keratoplasty (DSAEK) in eyes with previous glaucoma surgery. METHODS: This is a retrospective, comparative case series, including patients with previous trabeculectomy or glaucoma drainage device implantation, who later underwent either DMEK (n = 48) or DSAEK (n = 41). Follow-up was limited to 12 to 60 months to prevent bias. Primary outcomes were graft survival and rejection. Secondary outcomes were best spectacle-corrected visual acuity (BSCVA), detachment/rebubble, endothelial cell loss, and intraocular pressure elevations. RESULTS: Baseline characteristics, follow-up duration, and preexisting glaucoma parameters did not differ significantly between the groups. Graft survival probability after DMEK and DSAEK was 75% and 75% at 1 year, 63% and 50% at 2 years, 49% and 44% at 3 years, 28% and 33% at 4 years, and 28% and 29% at 5 years, respectively (P = 0.899 between the groups). Graft rejection rates were 20.8% and 19.5%, respectively (P = 1.000). Primary failure, rebubbling, endothelial cell loss, and intraocular pressure elevation did not differ significantly between the groups. Preoperative BSCVA did not differ between the groups (P = 0.821). Postoperative BSCVA was significantly better in the DMEK group at 6, 12, and 24 months (P < 0.001, P = 0.022, and P = 0.047, respectively). In a multivariable model (R2 = 0.576), the type of surgery was the only significant factor affecting postoperative BSCVA, in favor of DMEK (coefficient value -0.518, P = 0.002). CONCLUSIONS: In eyes with previous glaucoma surgery, DMEK and DSAEK had comparably low survival and comparably high rejection rates. Postoperative visual acuity might be better after DMEK in this setting.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it