Time to pars plana vitrectomy in adults with retained lens fragments: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To compare visual outcomes and complication risk based on the timing of pars plana vitrectomy (PPV) following cataract surgery with retained lens fragments. METHODS: MEDLINE (Ovid), EMBASE, and Cochrane Library were searched between 2000 to February 2022 for studies comparing visual outcomes and complications based on time to PPV. Discrete outcomes were analyzed using a random-effects meta-analysis model on Review Manager (RevMan 5.4). The certainty of evidence of outcomes was evaluated using the Grading of Recommendations, Assessment, Development and Evaluation approach. RESULTS: Ten studies and 1,693 eyes were included. The incidence of patients achieving a final best-corrected visual acuity (BCVA) of >6/12 Snellen may be similar among patients receiving PPV within 1 week or after 1 week of cataract surgery (RR = 1.06, 95% CI = [0.96, 1.17], p = 0.25), and patients receiving PPV within 1 month or after 1 month of cataract surgery (RR = 1.12, 95% CI = [0.95, 1.32]; p = 0.18). Incidence of glaucoma or elevated intraocular pressure for patients may be similar among patients receiving PPV within 1 week or after 1 week of cataract surgery (RR = 1.08, 95% CI = [0.62, 1.87]; p = 0.79), and patients receiving PPV within 1 month or after 1 month of cataract surgery (RR = 0.33, 95% CI = [0.09, 1.23]; p = 0.10). CONCLUSION: Incidence of patients achieving a final BCVA of >6/12 Snellen or postoperative adverse effects was similar between patients who underwent early and late PPV following cataract surgery. However, all studies had an overall serious risk of bias, primarily because of confounding and reporting bias.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.027 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".