Early Predictive Value of Different Indicators for Persistent Organ Failure in Acute Pancreatitis: A Systematic Review and Network Meta-Analysis.

Goals: In this study, we conducted this network meta-analysis (based on the ANOVA model) to evaluate the predictive efficacy of each early predictor.

Background: Persistent organ failure (POF) is one of the determining factors in patients with acute pancreatitis (AP); however, the diagnosis of POF has a long-time lag (>48 h). It is of great clinical significance for the early noninvasive prediction of POF.

Study: We conducted a comprehensive and systematic search in PubMed, Cochrane library, Embase, and Web of Science to identify relevant clinical trials, case-control studies, or cohort studies, extracted the early indicators of POF in studies, and summarized the predictive efficacy of each indicator through network meta-analysis. The diagnostic odds ratio (DOR) was used to rank the prediction efficiency of each indicator.

Results: We identified 23 studies in this network meta-analysis, including 10,393 patients with AP, of which 2014 patients had POF. A total of 10 early prediction indicators were extracted. The mean and 95% CI lower limit of each predictive indicator were greater than 1.0. Albumin had the largest diagnostic odds ratio, followed by high-density lipoprotein-cholesterol (HDL-C), Ranson Score, beside index for severity in acute pancreatitis Score, acute physiology and chronic health evaluation II, C-reactive protein (CRP), Interleukin 6 (IL-6), Interleukin 8 (IL-8), Systemic Inflammatory Response Syndrome (SIRS) and blood urea nitrogen.

Conclusions: Albumin, high-density lipoprotein-cholesterol, Ranson Score, and beside index for severity in acute pancreatitis Score are effective in the early prediction of POF in patients with AP, which can provide evidence for developing effective prediction systems. However, due to the limitations of the extraction method of predictive indicators in this study, some effective indicators may not be included in this meta-analysis.