Long-Term Redetachment Rates of Pneumatic Retinopexy versus Pars Plana Vitrectomy in Retinal Detachment
Bibliographic record
Abstract
PURPOSE: To assess long-term redetachment rates of the Pneumatic Retinopexy versus Vitrectomy for the Management of Primary Rhegmatogenous Retinal Detachment Outcomes Randomized Trial (PIVOT). DESIGN: Randomized controlled trial. SUBJECTS: PIVOT trial participants. METHODS: This study was performed at St. Michael's Hospital, Unity Health Toronto, Toronto, Canada. PIVOT trial participants who had undergone either pneumatic retinopexy (PnR) or pars plana vitrectomy (PPV) for rhegmatogenous retinal detachment (RRD) repair with a minimum follow-up of 2 years were assessed for long-term redetachment by chart review or telephone interview. The latter was the only accepted method for those with <2 years of follow-up. Patients were only eligible if no reintervention to reattach the retina was performed within the first year of the initial procedure. MAIN OUTCOME MEASURES: Long-term redetachment rates for PnR vs. PPV after RRD repair. RESULTS: Sixty-one participants who underwent PPV and 62 who underwent PnR were analyzed. The long-term redetachment rates were 0% and 1.61% (1/62) in the PPV and PnR groups, respectively (P = 0.32). The mean follow-up duration in years was 5.43 ± 3.60 vs. 5.51 ± 3.03 in the PPV and PnR groups, respectively. CONCLUSIONS: There was no statistically significant difference in long-term redetachment rates for PnR vs. PPV. Both procedures are durable treatment options for RRD over an extended period, rarely requiring additional intervention for redetachment. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".