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Differences in Bile Microbiology and Antibiotic Resistances between Liver Transplant Recipients and Non-Transplant Patients.

Background: Treatment of biliary infection in liver transplant (LT) recipients is a challenge, especially because of ineffectiveness of the antibiotic agents otherwise recommended for non-transplant populations. We aimed to understand the factors underlying the choice of antibiotic therapy. Patients and Methods: A total of 373 bile cultures from LT recipients with biliary complications (n = 127; LT group) and from a non-transplant population that underwent cholecystectomy for acute cholecystitis (n = 246; non-transplant group) between January 2009 and December 2018, were investigated. Results: Polymicrobial cultures (13.4% vs. 1.6%; p < 0.001), Enterococcus faecium (26.0% vs. 8.5%; p < 0.001), and Pseudomonas (13.4% vs. 4.1%; p = 0.001) in the LT group, and non-faecium enterococci (3.9% vs. 18.3%; p < 0.001) and Enterobacteriales (40.2% vs. 54.9%; p = 0.007), especially Escherichia (11.0% vs. 29.7%; p < 0.001), in the non-transplant group, showed higher abundance. Most of the antibiotic agents recommended as initial antibiotic therapy for the non-transplant population as per previous guidelines were not effective in LT recipients. The incidences of Enterococcus faecium (14.9% vs. 32.5%; p = 0.029) in the LT recipients with model for end-stage liver disease (MELD) score >12 and non-faecium enterococci (8.5% vs. 1.3%; p = 0.042) in those with MELD score ≤12 were higher than those in the other group. The incidence of Enterobacteriales increased over time after LT (p = 0.048) and was similar to that in the non-transplant group after one year of LT. Bile micro-organisms in LT recipients, resistant to most antibiotic agents, especially soon after LT changed over time and became similar to those in the non-transplant group after one year of LT. Conclusions: Antibiotic therapy for biliary infection in LT recipients should be different from that in non-transplant populations, considering clinical factors such as the time interval after LT and MELD score.