PARS PLANA VITRECTOMY-SUPRACHOROIDAL VISCOPEXY FOR RHEGMATOGENOUS RETINAL DETACHMENT REPAIR
Bibliographic record
Abstract
PURPOSE: To report reattachment rate of pars plana vitrectomy-suprachoroidal viscopexy (VIT-SCVEXY) for rhegmatogenous retinal detachment repair. In addition, this study compares the anatomic reattachment rate and functional outcomes of VIT-SCVEXY versus pars plana vitrectomy with traditional scleral buckle (PPV-SB) at postoperative month 3 and final follow-up. METHODS: A retrospective cohort study conducted at St. Michael's Hospital, Toronto, Canada, between 2023 and 2024. Consecutive cases of rhegmatogenous retinal detachment with inferior breaks were included, comparing outcomes between those who underwent VIT-SCVEXY (n = 12) versus PPV-SB (n = 12). Cases were matched for age, gender, lens status, retinal detachment characteristics, preoperative visual acuity, and follow-up duration. RESULTS: A suprachoroidal viscoelastic buckle was successfully created under the break(s) in 75.0% (9/12) of PPV-SCVEXY cases. The reattachment rate at 3 months in those with a successful suprachoroidal buckle was 100% (9/9), with a mean LogMAR best-corrected visual acuity of 0.75 ± 0.25 (Snellen 20/100). The reattachment rate for VIT-SCVEXY and PPV-SB cohorts at 3 months was 100% (12/12). At final follow-up, 88.8% (8/9) of patients who had PPV-SCVEXY remained attached, with an overall retinal reattachment rate of 91.6% (11/12) versus 100% (12/12) in the PPV-SB cohort, P = 1.0. Mean LogMAR VA was 0.7 ± 0.5 versus 0.7 ± 0.3 (Snellen 20/100), P = 0.9. Chemosis was observed in 25.0% (3/12) of VIT-SCVEXY cases, whereas no adverse events were recorded in PPV-SB cases. CONCLUSION: VIT-SCVEXY may be a less invasive alternative to PPV-SB with comparable anatomic and functional outcomes. However, further investigations are warranted.
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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 | 0.001 | 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) | 0.001 | 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".