Aqueous level abatement profiles of intracameral antibiotics: A comparative mathematical model of moxifloxacin, cefuroxime, and vancomycin with determination of relative efficacies
Bibliographic record
Abstract
PURPOSE: To create a model of the abatement profiles of the three most commonly employed endophthalmitis prophylaxis intracameral (IC) antibiotics-cefuroxime, vancomycin, and moxifloxacin-to enable comparison of their durations of efficacy against common endophthalmitis pathogens. SETTINGS: Humber River Hospital and The Eye Foundation of Canada, Toronto, Ontario, the University of Toronto, Ontario, and McGill University, Montreal, Quebec, Canada. DESIGN: Literature review, as well as review of our clinical experience with 4797 consecutive cases with IC vancomycin, followed by 9185 consecutive cases with IC moxifloxacin. METHODS: A detailed review of the prophylactic antibiotic literature was performed. Exponential decay models of the selected IC antibiotics were updated from previous work by the study authors with decay constants adjusted to agree with the available published objective data. RESULTS: The graphs generated by the study data demonstrate the relative duration of IC bactericidal activity of moxifloxacin, cefuroxime, and vancomycin. They suggest that at present, IC moxifloxacin, when administered in appropriate doses, is the most effective agent in preventing postoperative endophthalmitis. Unlike vancomycin and cefuroxime, bacterial resistance to moxifloxacin is dose-dependent, and it is overcome in the vast majority of cases with doses that can safely be achieved intracamerally. The graphs can serve as a useful tool to assess the expected efficacy of each antibiotic in reference to local pathogen resistances. CONCLUSION: The model shows IC moxifloxacin, cefuroxime, and vancomycin durations of bactericidal efficacy post-cataract surgery, which correlate well with the published objective data.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".