Comparative analysis of the safety and efficacy of intracameral cefuroxime, moxifloxacin and vancomycin at the end of cataract surgery: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Current practice methods are unclear as to the most safe and effective prophylactic pharmacotherapy and method of delivery to reduce postoperative endophthalmitis occurrence. METHODS: A systematic review and meta-analysis using Meta-analysis of Observational Studies in Epidemiology guidelines was performed to compare the efficacy of intracameral cefuroxime, moxifloxacin and vancomycin in preventing postphacoemulsification cataract surgery endophthalmitis. A safety analysis of intracameral antibiotics was concurrently performed. DATA SOURCES: BIOSIS Previews, CINAHL, ClinicalTrials.gov, Cochrane Library, Dissertations & Theses, EMBASE, PubMed, ScienceDirect and Scopus were searched from inception to January 2017. Data were pooled using a random effects model. All articles were individually reviewed and data were extracted by two independent reviewers. Funnel plot, risk of bias and quality of evidence analyses were performed. RESULTS: Seventeen studies with over 900 000 eyes were included, which favoured the use of intracameral antibiotics at the end of cataract surgery (OR 0.20; 95% CI 0.13 to 0.32; P<0.00001). The average weighted postoperative endophthalmitis incidence rates with intracameral cefuroxime, moxifloxacin and vancomycin were 0.0332%, 0.0153% and 0.0106%, respectively. Secondary analyses showed no difference in efficacy between intracameral plus topical antibiotics versus intracameral alone (P>0.3). Most studies had low to moderate risk of bias. The safety analysis showed minimal toxicity for moxifloxacin. Dosing errors led to the majority of toxicities with cefuroxime. Although rare, vancomycin was associated with toxic retinal events. CONCLUSION: Intracameral cefuroxime and moxifloxacin reduced endophthalmitis rates compared with controls with minimal or no toxicity events at standard doses. Additionally, intracameral antibiotics alone may be as effective as intracameral plus topical antibiotics.
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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 | 0.024 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.065 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".