Department of Infectious Diseases, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
J Int Med Res. 2020 May;48(5):300060520919220. doi: 10.1177/0300060520919220.
We aimed to analyze the risk factors and to establish a predictive tool for the occurrence of bloodstream infections (BSI) in patients with cirrhosis.
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.
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.
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.
本研究旨在分析肝硬化患者血流感染（BSI）发生的危险因素，并建立预测工具。
回顾性纳入 2888 例肝硬化患者。使用 logistic 回归分析 BSI 的危险因素。使用五重交叉验证验证多变量逻辑回归。
与 BSI 发生率独立相关的变量为白细胞计数（比值比[OR] = 1.094，95%置信区间[CI] 1.063-1.127）]、C 反应蛋白（OR = 1.005，95%CI 1.002-1.008）、总胆红素（OR = 1.003，95%CI 1.002-1.004）和先前的抗菌药物暴露（OR = 4.556，95%CI 3.369-6.160）；白蛋白（OR = 0.904，95%CI 0.883-0.926）、血小板计数（OR = 0.996，95%CI 0.994-0.998）和血清肌酐（OR = 0.989，95%CI 0.985-0.994）与较低的 BSI 发生几率相关。风险评估量表的受试者工作特征（ROC）曲线下面积为 0.850，其敏感性和特异性分别为 0.762 和 0.801。交叉验证和风险评估的 ROC 曲线之间没有显著差异。
我们为肝硬化患者开发了一种 BSI 预测工具，有助于在入院时早期识别此类感染，从而改善这些患者的预后。
