Endothelial keratoplasty versus repeat penetrating keratoplasty after failed penetrating keratoplasty: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: This study sought to compare graft survival, graft rejection and the visual acuity outcome of endothelial keratoplasty (EK) with repeat penetrating keratoplasty (PK) after failed PK. METHODS: A systematic literature search with subsequent screening of the identified articles was conducted to obtain potentially eligible randomized clinical trials (RCTs) and comparative cohort studies. To assess the methodological quality of the included studies, the Jadad Scale or Newcastle-Ottawa Scale (NOS) was used based on the study design. To calculate the pooled odds ratios (ORs) for graft survival, graft rejection and the visual acuity outcome with 95% confidential intervals (CIs), a fixed- or random-effects model was applied based on the heterogeneity across studies. RESULTS: Four comparative cohort studies (n = 649 eyes) comparing the outcome of EK with repeat PK after failed PK were included in this review. These studies were considered high quality, with NOS scores ranging from 6 to 9. The EK group showed a significantly lower risk of graft rejection than the repeat PK group [0.43 (95% CI: 0.23-0.80, P = 0.007)]. In addition, no significant differences were observed in a comparison of graft survival and visual acuity (P values ranged from 0.81 to 0.97 using the Der-Simonian and Laird random-effects model). CONCLUSIONS: As an alternative to repeat PK, EK after failed PK allows for potential reduction of the risk of graft rejection; however, it does not appear to confer a significant advantage in graft survival or visual acuity.
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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".