SURGICAL DRAINAGE METHODS DURING PARS PLANA VITRECTOMY FOR RHEGMATOGENOUS RETINAL DETACHMENT
Bibliographic record
Abstract
PURPOSE: To assess efficacy and safety outcomes of subretinal fluid drainage methods during pars plana vitrectomy for rhegmatogenous retinal detachment. METHODS: A systematic search strategy was conducted for studies published between January 2000 and October 2022. Included studies reported on either the safety or efficacy of two or more drainage methods during pars plana vitrectomy for patients with rhegmatogenous retinal detachment. RESULTS: Two randomized and five observational studies consisting of 1,524 eyes were included. Best-corrected visual acuity at the last study observation and primary reattachment rates were similar across groups. A significantly lower risk of epiretinal membrane formation was associated with draining subretinal fluid through preexisting retinal breaks (risk ratio = 0.70, 95% confidence interval = [0.60, 0.83], P = <0.01, I 2 = 0%) or with perfluorocarbon liquid (risk ratios = 0.70, 95% confidence interval = [0.59, 0.83], P = <0.01, I 2 = 0%) compared with posterior retinotomy. The risk of an abnormal foveal contour was significantly greater in perfluorocarbon liquid-treated eyes relative to posterior retinotomy (risk ratios = 1.56, 95% confidence interval = [1.13, 2.17], P = <0.01, I 2 = 0%). CONCLUSION: No significant differences were observed in the final best-corrected visual acuity at the last study observation and primary reattachment rates across different drainage methods. There remains limited information on the topic, so future research is warranted.
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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".