Establishing a Predictive Model for the Treatment Prognosis of Acute Pancreatitis Based on Biomarkers

Background and Objective: Acute pancreatitis is a common digestive system disease with poor clinical treatment effectiveness. The aim of this study was to explore the correlation between serum ApoB/ApoA1, CRP, lipase and other indicators with the severity of acute pancreatitis and to construct a predictive model for adverse prognosis risk. Person. Materials and Methods: The study enrolled 142 patients with acute pancreatitis (AP) who received a combination of octreotide and early enteral nutrition. Based on the follow-up results of 28 days, the patients were divided into two groups: Good prognosis and poor prognosis. Statistical analysis was conducted using SPSS 26.0. Draw a column chart model and calibration curve using the RMS package, use Stata to draw the model ROC curve and use the rmda program package in Rstudio to draw the clinical decision curve. Results: This study established a predictive model and the Bootstrap method resulted in a C-index of 0.884, indicating that the line chart risk prediction model has good predictive ability. The decision curve shows that the threshold probability range of the model is 0.01 similar to 1.00 and its net return rate is >0. Conclusion: High APACHE II score, elevated ApoB/ApoA1, elevated CRP and elevated LPS are independent risk factors for poor prognosis in AP patients treated with octreotide combined with early enteral nutrition. The risk prediction model constructed based on this has good predictive ability for poor prognosis in patients.