Revisiting the Evidence Base That Informs the Use of Adjunctive Therapy for <i>Enterococcus faecalis</i> Endocarditis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Guidelines recommend adjunctive gentamicin for the treatment of Enterococcus faecalis infective endocarditis (EFIE) despite a risk of toxicity. We sought to revisit the evidence for adjunctive therapy in EFIE and to synthesize the comparative safety and effectiveness of aminoglycosides versus ceftriaxone by systematic review and meta-analysis. METHODS: For historical context, we reviewed seminal case series and in vitro studies on the evolution from penicillin monotherapy to modern-day regimens for EFIE. Next, we searched MEDLINE and Embase from inception to 16 January 2024 for studies of EFIE that compared adjunctive aminoglycosides versus ceftriaxone or adjunctive versus monotherapy. Where possible, clinical outcomes were compared between regimens using random effects meta-analysis. Otherwise, data were narratively summarized. RESULTS: The meta-analysis was limited to 10 observational studies at high risk of bias (911 patients). Relative to adjunctive ceftriaxone, gentamicin had similar all-cause mortality (risk difference [RD], -0.8%; 95% confidence interval [CI], -5.0 to 3.5), relapse (RD, -0.1%; 95% CI, -2.4 to 2.3), and treatment failure (RD, 1.1%; 95% CI, -1.6 to 3.7) but higher discontinuation due to toxicity (RD, 26.3%; 95% CI, 19.8 to 32.7). The 3 studies that compared adjunctive therapy to monotherapy included only 30 monotherapy patients, and heterogeneity precluded meta-analysis. CONCLUSIONS: Adjunctive ceftriaxone appeared to be equally effective and less toxic than gentamicin for the treatment of EFIE. The existing evidence does not clearly establish the superiority of either adjunctive therapy or monotherapy. Pending randomized evidence, if adjunctive therapy is to be used, ceftriaxone appears to be a reasonable option.
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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 | 0.053 | 0.128 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.023 | 0.032 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".