Intra-abdominal infection in acute pancreatitis in eastern China: microbiological features and a prediction model

This study aimed to investigate the microbiol distribution of intra-abdominal infection in patients with acute pancreatitis, and to develop a reliable prediction model to guide the use of antibiotics.

Inpatient with acute pancreatitis between January 2015 and June 2020 were enrolled in the study. Participants were divided into the intra-abdominal infection group and non-infection group. Isolated pathogens and antibiotic susceptibility were documented. Characteristics parameters, laboratory results, and outcomes were also compared. Least absolute shrinkage and selection operator (LASSO) regression model was used to select the risk factors associated with intra-abdominal infection in patients with acute pancreatitis. Logistic regression analysis, random forest model, and artificial neural network were also used to validate the performance of the selected predictors in intra-abdominal infection prediction. A novel nomogram based on selected predictors was established to provide individualized risk of developing intra-abdominal infection in patients with acute pancreatitis.

A total amount of 711 participants were enrolled in the study, and of these, 182 (25.6%) had intra-abdominal infection. Of the 247 isolated pathogens, 45 (18.2%) were multidrug-resistant bacteria, and antibiotic susceptibility was lower than that of China Antimicrobial Surveillance Network 2020. The LASSO method identified 5 independent predictors [intra-abdominal pressure (IAP), acute physiology and chronic health evaluation II (APACHE II), computed tomography severity index (CTSI), the severity of pancreatitis, and intensive care unit (ICU) admission] of intra-abdominal infection, which were validated by three different models. The area under the curve was >0.95 for all 5 predictors. A clinically useful nomogram based on these predictors was successfully established.

Multidrug-resistant bacteria were quite common in intra-abdominal infection. IAP, APACHE II, CTSI, the severity of pancreatitis, and ICU admission were identified as risk factors and the new nomogram based on these could help clinicians estimate the risk of intra-abdominal infection and optimize antimicrobial prescription for acute pancreatitis patients.