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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

机译:预测印度人群急性胰腺炎的发病率和死亡率:BISAP评分Ranson评分和CT严重程度指数的比较研究

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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 population.>Methods: A total of 119 consecutive cases with acute pancreatitis were admitted to our institution between November 2012 and October 2014. BISAP scores were calculated for all cases, within 24 hours of presentation. Ranson’s score and computed tomography severity index (CTSI) were also established. The respective abilities of the three scoring systems to predict mortality was evaluated using trend and discrimination analysis. The 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%) died. The area under the curve (AUC) results for BISAP score in predicting SAP, PNec, and mortality were 0.962, 0.934 and 0.846, respectively. Ranson’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 0.958. The sensitivity and specificity of BISAP score, with a cut-off of ≥3 in predicting mortality, were 100% and 69.2%, respectively.>Conclusions: 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 severity. This risk stratification method can be utilized to improve clinical care and facilitate enrolment in clinical trials.
机译:>目的:我们的目的是在东部中部的一家三级医疗中心前瞻性评估床旁指数在急性胰腺炎(BISAP)评分中预测死亡率以及严重程度的中间指标的准确性印度,其主要服务对象是经济贫困的人群。>方法: 2012年11月至2014年10月间,我们机构共收治119例连续的急性胰腺炎病例。BISAP得分是在24小时的演讲。还建立了Ranson评分和计算机断层扫描严重度指数(CTSI)。使用趋势和判别分析评估了三种评分系统预测死亡率的能力。根据接受者操作特征(ROC)曲线得出的死亡率的最佳临界分值用于评估持续性器官衰竭和胰腺坏死(PNec)的发展。>结果:在119例病例中,有42例( 35.2%的人发展为器官衰竭,被分类为重症急性胰腺炎(SAP),47例(39.5%)发生PNec,12例(10.1%)死亡。预测SAP,PNec和死亡率的BISAP得分的曲线下面积(AUC)结果分别为0.962、0.934和0.846。 Ranson的分数显示出预测SAP(AUC 0.956)和死亡率(AUC 0.841)的准确性略低。 CTSI是预测PNec的最准确方法,AUC为0.958。 BISAP评分在预测死亡率时≥3的敏感性和特异性分别为100%和69.2%。>结论: BISAP评分代表了一种简单的识别方法,可在24岁以内就诊时间而言,患者死亡的风险更高,严重程度中间指标的发展也更高。此风险分层方法可用于改善临床护理并促进临床试验的注册。

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