Systematic review and meta-analysis of Densiron-68 anatomic outcomes and complications in the surgical management of retinal detachment
Bibliographic record
Abstract
OBJECTIVE: To summarize the anatomical reattachment rates, functional outcomes, and complications associated with Densiron-68 in retinal detachment (RD) surgery. METHODS: Following a systematic literature search, primary studies evaluating outcomes associated with Densiron-68 in adult RD surgery between January 2000 and May 2022 were included. Exclusion criteria included secondary studies, non-English language, and those in pediatric populations. The primary endpoints of interest were anatomical reattachment rate, and reported complications associated with Densiron-68. RESULTS: Twenty-eight studies (927 eyes) were included. Mean follow-up time was 41.9 weeks (IQR: 32.4-52.0 weeks). The weighted mean preoperative and postoperative BCVA was 1.38 ± 0.64 logMAR (20/500 Snellen) and 0.86 ± 0.55 logMAR (20/150 Snellen), respectively (p < 0.001). Anatomical reattachment rate after a single surgery was 72.5% overall (n = 672 eyes), with most redetachments occurring while Densiron-68 was in situ (46%; n = 81/255 eyes). Postoperatively, 29 complications were identified. The three most common were raised intraocular pressure (IOP) (n = 251 eyes; 27.1%), intraocular inflammation (n = 182 eyes; 19.6%), and emulsification (n = 160 eyes; 17.3%). Densiron-68 was significantly associated with an increased risk of elevated intraocular pressure postoperatively than traditional silicone oil (RR: 1.83 95% CI: 1.25-2.67; p = 0.001). The overall GRADE certainty of evidence for included studies was determined to be low due to the risk of bias, moderate imprecision in results due to wide confidence intervals, small studies, and few events within comparative studies, and moderate to high heterogeneity impacting consistency of evidence. CONCLUSIONS: Densiron-68 is a heavy silicone oil with clinical utility in retinal detachment surgery that has good primary anatomical reattachment rates and overall improvement in BCVA preoperatively to postoperatively. The authors highlight the anatomical and functional outcomes of Densiron-68 and the reported range of complications associated with its use, of which the majority were reversible or treatable with appropriate therapies.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.038 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".