Clinical Value Of A Severity Prediction Model Of Acute Pancreatitis (AP) Based On BISAP,MEWS And Routine Test Indexes

Objectives:To discuss the value of the Bedside Index for Severity in Acute Pancreatitis （BISAP）, Modified Early Warning Score （MEWS）, serum Ca²⁺ and red cell distribution width （RDW） for predicting the severity grade of acute pancreatitis and to develop and verify a more accurate scoring system to predict the severity of AP.Methods: In 302 patients with AP, we calculated BISAP and MEWS scores and conducted single factor logistic regression analyses on the relationships of BISAP scoring, RDW,MEWS,and serum Ca²⁺ with the severity of AP. The variables with statistical significance in the single factor logistic regression were used in a multi-factor logistic regression model; forward stepwise regression was used to screen variables and build a multi-factor prediction model. A Receiver Operating Characteristic curve （ROC curve） was constructed, and the significance of multi- and single-factor prediction models in predicting the severity of AP using the Area Under the ROC Curve （AUC） was evaluated. The internal validity of the model was verified through bootstrapping.Results: Among 302 patients with AP, 209 had mild acute pancreatitis （MAP）and 93 had severe acute pancreatitis （SAP）. According to single-factor logistic regression analysis, we found that BISAP, MEWS and serum Ca²⁺ are prediction indexes of the severity of AP （P value <0.001）, whereas RDW is not a prediction index of AP severity （P value >0.05）. The multi-factor logistic regression analysis showed that BISAP and serum Ca²⁺ are independent prediction indexes of AP severity（P value <0.001）, and MEWS is not an independent prediction index of AP severity（P value >0.05）.The predictive ability of each model for SAP follows the order of the combined BISAP and serum Ca²⁺ prediction model > serum Ca²⁺ > BISAP. There is no statistical significance for the predictive ability of BISAP and serum Ca²⁺ （P value>0.05）; however, there is remarkable statistical significance for the predictive ability using the newly built prediction model as well as BISAP and serum Ca²⁺individually（P value <0.01）. Verification of the internal validity of the models by bootstrapping is favorable.Conclusions: BISAP and serum Ca²⁺ have high predictive value for the severity of AP. However, the model built by combining BISAP and serum Ca²⁺ is remarkably superior to those of BISAP and serum Ca²⁺ individually. Furthermore, this model is simple, practical and appropriate for clinical use.