Abstract
BACKGROUND: Postdischarge morbidity and mortality is high in acute pancreatitis (AP) and pathophysiological mechanisms remain poorly understood. OBJECTIVES: We aim to investigate the composition of gut microbiota and clinical long-term outcomes of prospectively enrolled patients with AP to predict postdischarge complications. DESIGN: In this long-term follow-up study, we analysed clinical and microbiome data of 277 patients from the prospective multicentre Pancreatitis-Microbiome As Predictor of Severity trial. The primary endpoint was the association of the microbial composition with postdischarge mortality, recurrent AP (RAP), progression to chronic pancreatitis, pancreatic exocrine insufficiency, diabetes mellitus (DM) and pancreatic ductal adenocarcinoma. RESULTS: Buccal (n=238) and rectal (n=249) swabs were analysed by 16S rRNA and metagenomics sequencing using Oxford Nanopore Technologies. Median follow-up was 2.8 years. Distance-based redundancy analysis with canonical analysis of principal coordinates showed significant differences for β-diversity (Bray-Curtis) for postdischarge mortality (p=0.04), RAP (p=0.02) and DM (p=0.03). A ridge regression model including 11 differentially abundant species predicted postdischarge DM with an area under the receiving operating characteristic of 94.8% and 86.2% in the matched and entire cohort, respectively. Using this classifier, a positive predictive value of 66.6%, a negative predictive value of 96% and an accuracy of 95% was achieved. CONCLUSION: Our data indicate that the admission microbiome of patients with AP correlates with postdischarge complications independent from multiple risk factors such as AP severity, smoking or alcohol. Microbiota at admission show excellent capacity to predict postdischarge DM and may thus open new stratification tools for a tailored risk assessment in the future. TRIAL REGISTRATION NUMBER: NCT04777812.