Endoscopy-Assisted Vitrectomy Outcomes During Silicone Oil Removal After Complex Retinal Detachment Repair
Bibliographic record
Abstract
Purpose: This retrospective study recorded intraoperative findings during silicone oil removal and postoperative anatomical outcomes comparing endoscopy-assisted pars plana vitrectomy (E-PPV) vs pars plana vitrectomy (PPV) alone after proliferative vitreoretinopathy (PVR)-related retinal detachment (RD) repair. Methods: This single-center retrospective study included patients who underwent PPV for silicone oil removal after RD with PVR from July 2009 to January 2017. Patients with diabetic tractional RD, history of trauma, uveitis, or endophthalmitis were excluded. After 2013, an endoscopic visualization system (E2 MicroProbe; Endo Optiks) was used in a nonrandomized fashion. Data collection included reattachment rate, intraoperative endoscopic findings and phthisis rate. Results: Fifty-four eyes of 54 patients were included. The mean participant age was 58.4 ± 12.9 years and 36 (65.5%) participants were male. The mean (± SD) follow-up duration after oil removal was 24.3 ± 20.1 months. E-PPV combined with wide-angle visualization system was performed in 26 (48.1%) of the patients; the surgical management was modified after endoscopic examination in 17 (65.4%) of the cases. Reattachment rate in the E-PPV group was 96.2% compared with 76.0% in the PPV-alone group ( P = .04). Conclusions: E-PPV for silicone oil removal appears to be advantageous for prevention of RD recurrence, thus achieving better reattachment rates. A thorough examination is facilitated by endoscopic visualization and contributory factors for anterior PVR can be identified and treated.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".