Evaluation of the Prognostic Value of Existing Scoring Systems for Nosocomial Infection in Patients with Decompensated Liver Cirrhosis

Background: Many scoring systems have been developed to evaluate the severity and survival of end-stage liver disorder patients. However, the conduction of these different predicting models has not been thoroughly verified in cirrhotic patients with nosocomial infections. This study ended to compare the predictive accuracy of various scoring systems. Methods: During January 2015 and January 2020, liver cirrhosis patients with nosocomial infections were involved in this study. The clinical data, laboratory findings, and demographic characteristics of patients were collected during diagnosis. Patients were followed up for at least 6 months or till death. Results: One hundred thirty-one patients meeting the criteria were enrolled and followed up for at least 6 months. The mortality rate at 30 days, 3 months, and 6 months was 23%, 35.1%, and 39.6%, respectively. The univariate analysis showed that all scoring systems indicated statistical significance between the surviving group and the non-surviving group at 6 months. Model for end-stage liver disease-Na showed excellent predictive accuracy in predicting the survival at 30 days, 3 months, 6 months, with the area under the curve of 0.807, 0.850, and 0.844, respectively. Model for end-stage liver disease-Na demonstrated sensitivities of more than 85%. In contrast, the child-turcotte-pugh and albumin-bilirubin scores showed a poorer predictive capability. Conclusion: All 5 models for end-stage liver disease-related scores (model for end-stage liver disease, model for end-stage liver diseaseto-serum sodium ratio, model for end-stage liver disease-Na, model for end-stage liver disease-Delta, snd integrated model for endstage liver disease) exhibited a reliable prediction for mortality of long-term prognosis and short-term prognosis of cirrhotic patients with nosocomial infections. Among them, the model for end-stage liver disease-Na score might be the best choice.