RISK OF INTRAOCULAR INFLAMMATION AFTER INJECTION OF ANTIVASCULAR ENDOTHELIAL GROWTH FACTOR AGENTS
Bibliographic record
Abstract
PURPOSE: This meta-analysis investigates the incidence of intraocular inflammation (IOI) after intravitreal antivascular endothelial growth factor injections in neovascular age-related macular degeneration. METHODS: A systematic search was performed on Ovid MEDLINE, Embase, and Cochrane Central from January 2005 to April 2021. Randomized controlled trials comparing IOI after intravitreal bevacizumab, ranibizumab, brolucizumab, or aflibercept in neovascular age-related macular degeneration were included. Primary outcomes were sight-threatening IOI, final best-corrected visual acuity, and change in best-corrected visual acuity from baseline. Secondary outcomes included the incidence of other IOI events. Meta-analysis was performed using a random-effects model. RESULTS: Overall, 11,460 unique studies were screened, of which 14 randomized controlled trials and 6,759 eyes at baseline were included. There was no difference between agents for the risk of endophthalmitis and retinal vascular occlusion. Compared with aflibercept, brolucizumab had a higher incidence of generalized IOI (risk ratio = 6.24, 95% confidence interval = [1.40-27.90]) and vitreous haze/floaters (risk ratio = 1.64, 95% confidence interval = [1.00-2.67]). There were no significant differences between comparators for other secondary end points. CONCLUSION: There was no difference in the risk of severe sight-threatening IOI outcomes between intravitreal antivascular endothelial growth factor agents. There was a significantly higher risk of generalized IOI after brolucizumab relative to aflibercept. Our results alongside other recent safety findings suggest the need for further investigation in the risk-benefit profile of brolucizumab for the treatment of neovascular age-related macular degeneration.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.039 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".