Clinical Outcomes of Transscleral-Sutured Intraocular Lens Combined With Descemet Membrane Endothelial Keratoplasty
Bibliographic record
Abstract
PURPOSE: The aim of the study was to report clinical outcomes of Descemet membrane endothelial keratoplasty (DMEK) combined with transscleral-sutured intraocular lens (IOL) compared with DMEK combined with phacoemulsification and posterior chamber IOL (Phaco-DMEK). METHODS: A retrospective chart review of all patients who underwent DMEK combined with transscleral-sutured intraocular lens fixation or combined with phacoemulsification for Fuchs endothelial corneal dystrophy from 2016 to 2021 at the Toronto Western Hospital or the Kensington Eye Institute (Toronto, ON, Canada) and had at least 18 months of follow-up was performed. Main outcomes were postoperative distance-corrected visual acuity, rebubbling rate, graft survival rate, and complications. RESULTS: Twenty-one cases of DMEK combined with transscleral-sutured IOL (DMEK-TSS-IOL) and 44 cases of Phaco-DMEK were evaluated. Twelve eyes (57.15%) had a foldable acrylic 3-piece IOL (AR40E) and 9 (42.85%) had a single-piece polymethylmethacrylate (PMMA) IOL (CZ70BD). LogMAR distance-corrected visual acuity improved significantly from 1.48 ± 0.62 (SD) to 0.86 ± 0.82 ( P = 0.01) 12 months after DMEK-TSS-IOL and from 0.41 ± 0.29 logMAR to 0.11 ± 0.11 logMAR ( P < 0.0001) after Phaco-DMEK. No statistically significant differences were observed in donor ( P = 0.97) or 1-year postoperative endothelial cell density ( P = 0.11) between the groups. Rebubbling was necessary in 33.33% of eyes in DMEK-TSS-IOL compared with 25% of Phaco-DMEK eyes ( P = 0.55). Graft survival rate was 76.19% in the DMEK-TSS-IOL group compared with 90.90% in the Phaco-DMEK group ( P = 0.13). CONCLUSIONS: Transscleral-sutured IOL combined with DMEK is an option for the management of endothelial diseases in aphakic eyes or those which require IOL exchange for the experienced surgeon. However, when compared with routine Phaco-DMEK, there are higher complication and lower survival rates at 18 months.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".