Prefilled syringes and post-intravitreal injection endophthalmitis: A network meta-analysis
Bibliographic record
Abstract
Optimally, syringe-filling technique may reduce the risk of post-injection endophthalmitis (PIE), yet there is wide variation between ophthalmologists and jurisdictions regarding syringe-filling practices. This frequentist network meta-analysis (PROSPERO: CRD42024555196) of rare events sought to compare the odds of PIE between manufactured prefilled syringes (PFS), compounded syringes, and traditional vial preparation of syringes (VPS) for intravitreal anti-vascular endothelial growth factor therapy. Given outcome rarity, we included studies whose primary outcome was PIE incidence. From 20 observational studies (3746 PIE events; 41,611,960 injections), the odds of PIE were significantly lower with PFS (OR: 0.45, 95 % confidence interval [CI]: 0.40-0.49) and compounded syringes (OR: 0.69, 95 % CI: 0.64-0.74) compared to VPS. The odds of PIE were significantly lower with PFS compared to compounded syringes (OR: 0.65, 95 % CI: 0.58-0.72). The odds of culture-positive PIE were significantly lower with PFS than both VPS (OR: 0.15, 95 % CI: 0.06-0.41) and compounded syringes (OR: 0.15, 95 % CI: 0.05-0.44). No significant difference in culture-positive PIE was observed between VPS and compounded syringes (OR: 1.02, 95 % CI: 0.66-1.58). Low certainty evidence supports that PFS significantly reduce the rate of clinical and culture-positive PIE compared to VPS and compounded syringes. Future studies should further characterize the role of confounding.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.038 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".