Development of ocular hypertension secondary to tamponade with light versus heavy silicone oil: A systematic review
Bibliographic record
Abstract
AIM: The intraocular silicone oil (SO) tamponades used in the treatment of retinal detachment (RD) have been associated with a difference ocular hypertension (OH) rate. To clarify, if this complication was associated to use of standard SO (SSO) versus heavy SO (HSO), we performed a systematic review and meta-analysis of comparative study between two kind of SO (standard or light vs. heavy) for the treatment of RD and macular hole, without restriction to study design. MATERIALS AND METHODS: The methodological quality of two randomized clinical trials (RCTs) were evaluated using the criteria given in the Cochrane Handbook for Systematic Reviews of Intervention, while three non-RCTs were assessed with the Newcastle-Ottawa Scale and Strengthening the Reporting of Observational Studies in Epidemiology checklists. We calculated Mantel-Haenszel risk ratio (RR) with 95% confidence intervals (95% CIs). The primary outcome was the rate of patients with OH treated with SSO compared to HSO. RESULTS: There were a higher number of rates of OH in HSO compared to SSO. This difference was statistically significant with the fixed effect model (Mantel-Haenszel RR; 1.55; 95% CI, 1.06-2.28; P = 0.02) while there was not significative difference with the random effect model (Mantel-Haenszel RR; 1.51; 95% CI, 0.98-2.33; P = 0.06). CONCLUSION: We noted a trend that points out a higher OH rate in HSO group compared to SSO, but this finding, due to the small size and variable design of studies, needs to be confirmed in well-designed and large size RCTs.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".