What is the optimal antimicrobial prophylaxis to prevent postoperative infectious complications after liver transplantation? A systematic review of the literature and expert panel recommendations
Bibliographic record
Abstract
BACKGROUND: Antimicrobial prophylaxis is well-accepted in the liver transplant (LT) setting. Nevertheless, optimal regimens to prevent bacterial, viral, and fungal infections are not defined. OBJECTIVES: To identify the optimal antimicrobial prophylaxis to prevent post-LT bacterial, fungal, and cytomegalovirus (CMV) infections, to improve short-term outcomes, and to provide international expert panel recommendations. DATA SOURCES: Ovid MEDLINE, Embase, Scopus, Google Scholar, and Cochrane Central. METHODS: Systematic review following PRISMA guidelines and recommendations using the GRADE approach derived from an international expert panel. PROSPERO ID: CRD42021244976. RESULTS: Of 1853 studies screened, 34 were included for this review. Bacterial, CMV, and fungal antimicrobial prophylaxis were evaluated separately. Pneumocystis jiroveccii pneumonia (PJP) antimicrobial prophylaxis was analyzed separately from other fungal infections. Overall, eight randomized controlled trials, 21 comparative studies, and five observational noncomparative studies were included. CONCLUSIONS: Antimicrobial prophylaxis is recommended to prevent bacterial, CMV, and fungal infection to improve outcomes after LT. Universal antibiotic prophylaxis is recommended to prevent postoperative bacterial infections. The choice of antibiotics should be individualized and length of therapy should not exceed 24 hours (Quality of Evidence; Low | Grade of Recommendation; Strong). Both universal prophylaxis and preemptive therapy are strongly recommended for CMV prevention following LT. The choice of one or the other strategy will depend on individual program resources and experiences, as well as donor and recipient serostatus. (Quality of Evidence; Low | Grade of Recommendation; Strong). Antifungal prophylaxis is strongly recommended for LT recipients at high risk of developing invasive fungal infections. The drug of choice remains controversial. (Quality of Evidence; High | Grade of Recommendation; Strong). PJP prophylaxis is strongly recommended. Length of prophylaxis remains controversial. (Quality of Evidence; Very Low | Grade of Recommendation; Strong).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".