Predicting morbidity and mortality in acute pancreatitis in an Indian population:a comparative study of the BISAP score,Ranson’s score and CT severity index

作     者：Jitin Yadav Sanjay Kumar Yadav Satish Kumar Ranjan George Baxla Dipendra Kumar Sinha Pankaj Bodra Ram Chandra Besra Babu Mani Baski Om Prakash Abhinav Anand 

作者机构：Department of General SurgeryRajendra Institute of Medical SciencesRanchiJharkhandIndia 

出 版 物：《Gastroenterology Report》 (胃肠病学报道（英文）)

年 卷 期：2016年第4卷第3期

页      面：216-220,I0002页

核心收录：

学科分类：1002[医学-临床医学] 100201[医学-内科学(含：心血管病、血液病、呼吸系病、消化系病、内分泌与代谢病、肾病、风湿病、传染病)] 10[医学] 

主　　题：acute pancreatitis mortality bedside index for severity in acute pancreatitis(BISAP) Ranson’s score computed tomography severity index(CTSI) 

摘      要：Objective:Our aim was to prospectively evaluate the accuracy of the bedside index for severity in acute pancreatitis(BISAP)score in predicting mortality,as well as intermediate markers of severity,in a tertiary care centre in east central India,which caters mostly for an economically underprivileged ***:A total of 119 consecutive cases with acute pancreatitis were admitted to our institution between November 2012 and October *** scores were calculated for all cases,within 24 hours of ***’s score and computed tomography severity index(CTSI)were also *** respective abilities of the three scoring systems to predict mortality was evaluated using trend and discrimination *** optimal cut-off score for mortality from the receiver operating characteristics(ROC)curve was used to evaluate the development of persistent organ failure and pancreatic necrosis(PNec).Results:Of the 119 cases,42(35.2%)developed organ failure and were classified as severe acute pancreatitis(SAP),47(39.5%)developed PNec,and 12(10.1%)*** area under the curve(AUC)results for BISAP score in predicting SAP,PNec,and mortality were 0.962,0.934 and 0.846,***’s score showed a slightly lower accuracy for predicting SAP(AUC 0.956)and mortality(AUC 0.841).CTSI was the most accurate in predicting PNec,with an AUC of *** sensitivity and specificity of BISAP score,with a cut-off of≥3 in predicting mortality,were 100%and 69.2%,***:The BISAP score represents a simple way of identifying,within 24 hours of presentation,patients at greater risk of dying and the development of intermediate markers of *** risk stratification method can be utilized to improve clinical care and facilitate enrolment in clinical trials.