Background: Identification of patients at risk for mortality early in the course of acute pancreatitis (AP) is an important step in improving outcome. Methods: Using Classification and Regression Tree (CART) analysis, a clinical scoring system was developed for prediction of in-hospital mortality in AP. The scoring system was derived on data collected from 17 992 cases of AP from 212 hospitals in 2000-2001. The new scoring system was validated on data collected from 18 256 AP cases from 177 hospitals in 2004-2005. The accuracy of the scoring system for prediction of mortality was measured by the area under the receiver operating characteristic curve (AUC). The performance of the new scoring system was further validated by comparing its predictive accuracy with that of Acute Physiology and Chronic Health Examination (APACHE) II. Results: CART analysis identified five variables for prediction of in-hospital mortality. One point is assigned for the presence of each of the following during the first 24 h: blood urea nitrogen (BUN) >25 mg/dl; impaired mental status; systemic inflammatory response syndrome (SIRS); age >60 years; or the presence of a pleural effusion (BISAP). Mortality ranged from >20% in the highest risk group to <1% in the lowest risk group. In the validation cohort, the BISAP AUC was 0.82 (95% Cl 0.79 to 0.84) versus APACHE II AUC of 0.83 (95% Cl 0.80 to 0.85). Conclusions: A new mortality-based prognostic scoring system for use in AP has been derived and validated. The BISAP is a simple and accurate method for the early identification of patients at increased risk for in-hospital mortality.

The early prediction of mortality in acute pancreatitis : a large population-based study. Commentary

Objective Our aim was to prospectively compare the Accuracy of Acute Physiology and Chronic Health Evaluation (APACHE) II, Bedside Index of Severity in Acute Pancreatitis (BISAP), Ranson's score and modified Computed Tomography Severity Index (CTSI) in predicting the severity of acute pancreatitis based on Atlanta 2012 definitions in a tertiary care hospital in northern India. Methods Fifty patients with acute pancreatitis admitted to our hospital during the period of March 2015 to September 2016 were included in the study. APACHE II, BISAP and Ranson's score were calculated for all the cases. Modified CTSI was also determined based on a pancreatic protocol contrast enhanced computerized tomography (CT). Optimal cut-offs for these scoring systems and the area under the curve (AUC) were evaluated based on the receiver operating characteristics (ROC) curve and these scoring systems were compared prospectively. Results Of the 50 cases, 14 were graded as severe acute pancreatitis. Pancreatic necrosis was present in 15 patients, while 14 developed persistent organ failure and 14 needed intensive care unit (ICU) admission. The AUC for modified CTSI was consistently the highest for predicting severe acute pancreatitis (0.919), pancreatic necrosis (0.993), organ failure (0.893) and ICU admission (0.993). APACHE II was the second most accurate in predicting severe acute pancreatitis (AUC 0.834) and organ failure (0.831). APACHE II had a high sensitivity for predicting pancreatic necrosis (93.33%), organ failure (92.86%) and ICU admission (92.31%), and also had a high negative predictive value for predicting pancreatic necrosis (96.15%), organ failure (96.15%) and ICU admission (95.83%). Conclusion APACHE II is a useful prognostic scoring system for predicting the severity of acute pancreatitis and can be a crucial aid in determining the group of patients that have a high chance of need for tertiary care during the course of their illness and therefore need early resuscitation and prompt referral, especially in resource-limited developing countries.

/pdf/a-comparison-of-apache-ii-bisap-ranson-s-score-and-modified-2tocozswfk.pdf

A comparison of APACHE II, BISAP, Ranson’s score and modified CTSI in predicting the severity of acute pancreatitis based on the 2012 revised Atlanta Classification

Background: The management of the moderate and severe forms of acute pancreatitis (AP) with necrosis and multiorgan failure remains a challenge. To predict the severity and mortality of AP multiple clinical, laboratory-, and imaging-based scoring systems are available. Aim: To investigate, if the computed tomography severity index (CTSI) can predict the outcomes of AP better than other scoring systems. Methods: A systematic search was performed in three databases: Pubmed, Embase, and the Cochrane Library. Eligible records provided data from consecutive AP cases and used CTSI or modified CTSI (mCTSI) alone or in combination with other prognostic scores [Ranson, bedside index of severity in acute pancreatitis (BISAP), Acute Physiology, and Chronic Health Examination II (APACHE II), C-reactive protein (CRP)] for the evaluation of severity or mortality of AP. Area under the curves (AUCs) with 95% confidence intervals (CIs) were calculated and aggregated with STATA 14 software using the metandi module. Results: Altogether, 30 studies were included in our meta-analysis, which contained the data of 5,988 AP cases. The pooled AUC for the prediction of mortality was 0.79 (CI 0.73-0.86) for CTSI; 0.87 (CI 0.83-0.90) for BISAP; 0.80 (CI 0.72-0.89) for mCTSI; 0.73 (CI 0.66-0.81) for CRP level; 0.87 (CI 0.81-0.92) for the Ranson score; and 0.91 (CI 0.88-0.93) for the APACHE II score. The APACHE II scoring system had significantly higher predictive value for mortality than CTSI and CRP (p = 0.001 and p < 0.001, respectively), while the predictive value of CTSI was not statistically different from that of BISAP, mCTSI, CRP, or Ranson criteria. The AUC for the prediction of severity of AP were 0.80 (CI 0.76-0.85) for CTSI; 0.79, (CI 0.72-0.86) for BISAP; 0.83 (CI 0.75-0.91) for mCTSI; 0.73 (CI 0.64-0.83) for CRP level; 0.81 (CI 0.75-0.87) for Ranson score and 0.80 (CI 0.77-0.83) for APACHE II score. Regarding severity, all tools performed equally. Conclusion: Though APACHE II is the most accurate predictor of mortality, CTSI is a good predictor of both mortality and AP severity. When the CT scan has been performed, CTSI is an easily calculable and informative tool, which should be used more often in routine clinical practice.

/pdf/computed-tomography-severity-index-vs-other-indices-in-the-5fveegiycx.pdf

Computed Tomography Severity Index vs. Other Indices in the Prediction of Severity and Mortality in Acute Pancreatitis: A Predictive Accuracy Meta-analysis

Background Early and accurate evaluation of severity and prognosis in acute pancreatitis (AP), especially at the time of admission is very significant This study was aimed to develop an artificial neural networks (ANN) model for early prediction of in-hospital mortality in AP Methods Patients with AP were identified from the Medical Information Mart for Intensive Care-III (MIMIC-III) database Clinical and laboratory data were utilized to perform a predictive model by back propagation ANN approach Results A total of 337 patients with AP were analyzed in the study, and the in-hospital mortality rate was 112% A total of 12 variables that differed between patients in survivor group and nonsurvivor group were applied to construct ANN model Three independent variables were identified as risk factors associated with in-hospital mortality by multivariate logistic regression analysis The predictive performance based on the area under the receiver operating characteristic curve (AUC) was 0769 for ANN model, 0607 for logistic regression, 0652 for Ranson score, and 0401 for SOFA score Conclusion An ANN predictive model for in-hospital mortality in patients with AP in MIMIC-III database was first performed The patients with high risk of fatal outcome can be screened out easily in the early stage of AP by our model

/pdf/an-artificial-neural-networks-model-for-early-predicting-in-2hiqwcnf6h.pdf

An Artificial Neural Networks Model for Early Predicting In-Hospital Mortality in Acute Pancreatitis in MIMIC-III.

Background: predicting the development of severe disease has remained a major challenge in management of acute pancreatitis. The Bedside Index for Severity in Acute Pancreatitis (BISAP) is easy to calculate from the data available in the first 24 hours. Here, we performed a systematic review to determine the prognostic accuracy of the BISAP for severe acute pancreatitis (SAP). Methods: major databases of biomedical publications were searched during the first week of October 2015. Two independent reviewers searched records in two phases. Studies that reported prognostic accuracy of the BISAP for SAP from prospective cohorts were included. The pooled area under the receiver operating curve (AUC) was calculated. Results: Twelve studies were included for data-synthesis and methodology quality assessment was performed for 10. All the studies had enrolled consecutive patients, had a broad spectrum of the disease severity, reported explicit interpretation of the predictor, outcome of interest was well defined and had adequate follow-up. Blinded outcome assessment was reported in only one study. The pooled AUC was 0.85 (95% CI 0.80-0.90). There was significant heterogeneity, I2 86.6%. Studies using revised Atlanta classification in defining SAP had a pooled AUC of 0.92 (95% CI, 0.90-0.95), but heterogeneity persisted, I2 67%. Subgroup analysis based on rate of SAP (>20% vs <20%) did not eliminate the heterogeneity. Conclusion: the BISAP has very good predictive performance for SAP across different patient population and etiologies. Studies to evaluate the impact of incorporating the BISAP into clinical practice to improve outcome in acute pancreatitis are needed before adoption could be advocated with confidence.

https://www.tandfonline.com/doi/pdf/10.1080/20009666.2017.1361292

The Bedside Index for Severity in Acute Pancreatitis: a systematic review of prospective studies to determine predictive performance.

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.

/pdf/predicting-morbidity-and-mortality-in-acute-pancreatitis-in-3mq20w900q.pdf

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

Ram Chandra Besra

Papers

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