Clinical risk factors and predictive tool of bacteremia in patients with cirrhosis

• Published in: Journal of international medical research 2020-05, Vol.48 (5), p.300060520919220-300060520919220
• Main Authors: Yang, Qiao, Jiang, Xian Zhong, Zhu, Yong Fen, Lv, Fang Fang
• Format: Article
• Language: English
• Subjects: Adult; Aged; Bacteremia - epidemiology; Bacteremia - immunology; Bilirubin - blood; C-Reactive Protein - analysis; Creatinine - blood; Female; Hospitalization; Humans; Incidence; Liver cirrhosis; Liver Cirrhosis - blood; Liver Cirrhosis - complications; Liver Cirrhosis - immunology; Logistic Models; Male; Middle Aged; Platelet Count; Retrospective Clinical Research Report; Retrospective Studies; Risk assessment; Risk Assessment - methods; Risk Factors; ROC Curve; Serum Albumin, Human - analysis
• ISSN: 0300-0605; 1473-2300
• DOI: 10.1177/0300060520919220

Objective We aimed to analyze the risk factors and to establish a predictive tool for the occurrence of bloodstream infections (BSI) in patients with cirrhosis. Methods A total of 2888 patients with cirrhosis were retrospectively included. Multivariate analysis for risk factors of BSI were tested using logistic regression. Multivariate logistic regression was validated using five-fold cross-validation. Results Variables that were independently associated with incidence of BSI were white blood cell count (odds ratio [OR] = 1.094, 95% confidence interval [CI] 1.063–1.127)], C-reactive protein (OR = 1.005, 95% CI 1.002–1.008), total bilirubin (OR = 1.003, 95% CI 1.002–1.004), and previous antimicrobial exposure (OR = 4.556, 95% CI 3.369–6.160); albumin (OR = 0.904, 95% CI 0.883–0.926), platelet count (OR = 0.996, 95% CI 0.994–0.998), and serum creatinine (OR = 0.989, 95% CI 0.985–0.994) were associated with lower odds of BSI. The area under receiver operating characteristic (ROC) curve of the risk assessment scale was 0.850, and its sensitivity and specificity were 0.762 and 0.801, respectively. There was no significant difference between the ROC curves of cross-validation and risk assessment. Conclusions We developed a predictive tool for BSI in patients with cirrhosis, which could help with early identification of such episodes at admission, to improve outcome in these patients.