ASSOCIATION BETWEEN ANTIBIOTIC PROPHYLAXIS AND ENDOPHTHALMITIS AFTER INTRAVITREAL INJECTION
Bibliographic record
Abstract
PURPOSE: To compare the incidence of endophthalmitis after intravitreal injection with versus without topical antibiotic prophylaxis. METHODS: We systematically searched PubMed, Embase, and the Cochrane Library from each database's inception through August 2024. The primary outcome measure was the endophthalmitis rates after intravitreal injection, whereas the secondary outcomes included the distribution and quantity of microorganisms and best-corrected visual acuity changes. Study quality was assessed using the Newcastle-Ottawa Scale. For the meta-analysis, pooled summary estimates were calculated using a random-effects model. RESULTS: Eighteen studies (3,138,778 intravitreal injections; 1,426 endophthalmitis cases) showed no significant difference in endophthalmitis incidence between prophylaxis and no-prophylaxis groups (odds ratio 1.85, 95% confidence interval [CI] 0.72‒4.76; P = 0.2). For microbial analysis, we selected 11 studies that demonstrated no significant difference in culture-positive rates between prophylaxis and nonprophylaxis groups (OR, 1.23; 95% CI, [0.53‒2.84]; P = 0.63). Four studies provided best-corrected visual acuity changes from baseline to final follow-up, antibiotic prophylaxis group showed a decrease by 4.5 ETDRS letters compared with the no-prophylaxis group, although this difference was not statistically significant ( P = 0.65). CONCLUSION: Topical antibiotics did not reduce endophthalmitis risk or improve visual outcomes postintravitreal injection. Given potential risks, routine prophylaxis is not recommended.
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".