Impact of Vancomycin-Resistant <i>Enterococci</i> (VRE)–Active Perioperative Prophylaxis in Liver Transplant Patients Colonized by VRE
Bibliographic record
Abstract
BACKGROUND: Data regarding the effectiveness of vancomycin-resistant Enterococci (VRE)-active prophylaxis for preventing early post-liver transplantation (LT) VRE infections in VRE-colonized patients are scarce. METHODS: 131 pre-LT VRE-colonized patients who underwent LT were enrolled in a retrospective, observational, multicenter study. The incidence of early-onset VRE infections was compared between patients who received active prophylaxis for VRE and those who did not. RESULTS: Sixty-nine (52.7%) and 62 (47.3%) patients were enrolled in the VRE-active and non-VRE-active prophylaxis group. Tigecycline was the most common drug prescribed as VRE-active for prophylaxis (55/69; 79.7%). There was no significant difference in the number of patients who developed early-onset VRE infections in the VRE-active versus non-VRE-active groups at 7 (0 [0.0%] vs 2 [3.2%]; P = .222), 14 (4 [5.7%] vs 4 [6.4%]; P = 1.000), and 30 (6 [8.7%] vs 8 [12.9%]; P = .621) days post-LT, respectively. Risk of early-onset VRE infection within 30 days was not lower in the VRE-active group (log-rank P = .16 with Kaplan-Meier analysis; odds ratio [OR]: .643; 95% CI: .210-1.969; P = .439 with univariate analysis). Conversely, early infections caused by any pathogen were significantly lower in the VRE-active prophylaxis group compared with the control group (11 [15.9%] vs 20 [32.2%]; P = .047). Tigecycline prophylaxis was associated with a lower risk of early-onset infections with multivariate analysis (OR: .106; 95% CI: .015-.745; P = .024) and after adjusting for propensity score (adjusted OR: .146; 95% CI: .031-.708; P = .017). CONCLUSIONS: VRE-active prophylaxis at LT did not reduce the incidence of early post-LT VRE infections and should not be recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".