Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes

Background: Spontaneous bacterial peritonitis (SBP) is a common complication in patients with cirrhosis, but the biomarkers for diagnosis have yet to be validated. This study aimed to identify reliable and easy-to-use biomarkers for the diagnosis and prognosis of cirrhotic patients with complicated SBP. Methods Cirrhosis data were collected retrospectively; The clinical features and laboratory test indices were analyzed. The indices related to the SBP of cirrhosis were analyzed. Two machine learning methods (Xgboost and LASSO algorithms) and a logistic regression analysis were adopted to screen and validate the indexed risk associated with SBP risk, then a predictive model was built and validated using the area under curve (AUC) estimated. The indices related to the survival of cirrhotic patients were also analyzed. Results A total of 413 cirrhotic patients were included, of whom 329 were decompensated and 84 were compensated. 52 patients complicated SPB and they were all decompensated patients. Patients with SBP have a poorer Child-Pugh score (P < 0.05) and the proportion of cancers was higher in patients with SBP than in those without SBP (P < 0.05). Most laboratory test indices differed significantly between patients with and without SBP (P < 0.05). Xgboost, LASSO algorithms, and logistic regression analysis identified that albumin, neutrophil-to-lymphocyte ratio (NLR), and ferritin-to-neutrophil ratio (FNR) were independently associated with SBP in uncompensated cirrhotic patients, and that established by the three indices model showed a high predictive value. with the AUC being 0.808. In addition, high neutrophils, ALP and CAR were associated with the shorter survival time of patients with decompensated cirrhosis, and the combination of these indices showed a better prognostic value for cirrhotic patients. Conclusions The present study identified FNR as a new index in the diagnosis of SBP in uncompensated patients with cirrhosis. A model constructed from neutrophils, ALP and CAR showed high performance in predicting the prognosis of patients with uncompensated cirrhosis.