Abstract
Background: Infection in acute on chronic liver failure (ACLF) patients is known to cause higher mortality. The current approach is to culture all patients. We aim to identify clinical factors predictive of infections within ACLF patients and to assess compliance to obtain diagnostic work up within 24 hours of hospital admission. Methods: We retrospectively analyzed the charts of 457 adult, ACLF patients seen at the University of Arizona, all campuses, between January 1, 2014 and December 31, 2014. We used logistic regression to identify potential risk indicators for bacterial, fungal, and any infections. Findings: 60.61% of patients were identified with established infection. Systemic inflammatory response syndrome (SIRS) criteria alone predicted infections in ACLF patients with C-statistic of 0.71 (OR 6.85, 95% CI: 4.33, 10.85) for any infection, 0.63 (OR 2.88, 95% CI: 1.96, 4.23) for bacterial infection, and 0.53 (OR 1.32, 95% CI: 0.59, 2.96) for fungal infection. After controlling for other significant variables, predictive ability improved, C-statistic 0.83 (95% CI: 0.77, 0.90) for any infection and 0.71 (95% CI: 0.65, 0.77) for bacterial infections. Combination of MELD and Hb predicted fungal infections with C-statistic 0.74 (95% CI: 0.63, 0.84). Basic work up within 24 hours of admission was obtained in 12% of patients. Interpretation: SIRS criteria alone poorly predicts infections in ACLF patients. The addition of other factors moderately improves predictions. Compliance is very poor to obtain diagnostic work up efficiently, and better tools are needed to predict infection upon admission. Funding Statement: This research was funded by Liver Institute PLLC. Declaration of Interests: The authors have no conflicts of interest to disclose. Ethics Approval Statement: The University of Arizona’s Institutional Review Board approved the study protocol. The patient consent requirement was waived by the Institutional Review Board. We followed the ethical guidelines set forth by the 1975 Declaration of Helsinki.
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