Prophylaxis for infective endocarditis. Who needs it? How effective is it?
Bibliographic record
Abstract
OBJECTIVE: To review guidelines for using antibiotic prophylaxis to prevent infective endocarditis, and to present recent changes and controversies regarding these guidelines. QUALITY OF EVIDENCE: Data are from physiologic and in vitro studies, as well as studies of animal models, and from retrospective analyses of human endocarditis cases. Systematic reviews and guidelines are also examined. As no randomized clinical trials have examined prophylaxis for bacterial endocarditis, many recommendations presented are based on consensus guidelines. MAIN MESSAGE: Antibiotic prophylaxis to prevent bacterial endocarditis should be used in high- and moderate-risk patients with cardiac disease. It should be given before procedures in which bacteremias are likely with organisms that cause endocarditis, such as viridans streptococci. For most procedures, a single dose of amoxicillin (2 g by mouth 1 hour before the procedure) is sufficient to ensure adequate serum levels before and after the procedure. CONCLUSION: Infective endocarditis continues to have high rates of morbidity and mortality. Antibiotic prophylaxis, therefore, is important to combat this preventable disease. For high- and moderate-risk patients with cardiac disease, the cost-benefit ratio favours prophylaxis.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".