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

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TLDR
The BISAP is a simple and accurate method for the early identification of patients at increased risk for in-hospital mortality in acute pancreatitis.
Abstract
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 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.

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Citations
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Journal ArticleDOI

Classification of acute pancreatitis—2012: revision of the Atlanta classification and definitions by international consensus

TL;DR: This international, web-based consensus provides clear definitions to classify acute pancreatitis using easily identified clinical and radiologic criteria and should encourage widespread adoption.
Journal ArticleDOI

American College of Gastroenterology guideline: management of acute pancreatitis.

TL;DR: As the diagnosis of AP is most often established by clinical symptoms and laboratory testing, contrast-enhanced computed tomography and/or magnetic resonance imaging of the pancreas should be reserved for patients in whom the diagnosis is unclear or who fail to improve clinically.
Journal ArticleDOI

Comparison of BISAP, Ranson's, APACHE-II, and CTSI scores in predicting organ failure, complications, and mortality in acute pancreatitis

TL;DR: It is confirmed that the BISAP score is an accurate means for risk stratification in patients with AP and simple scoring systems may have reached their maximal utility and novel models are needed to further improve predictive accuracy.
References
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Journal ArticleDOI

Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.

TL;DR: A nonparametric approach to the analysis of areas under correlated ROC curves is presented, by using the theory on generalized U-statistics to generate an estimated covariance matrix.
Book

Classification and regression trees

Leo Breiman
TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
Journal ArticleDOI

APACHE II: a severity of disease classification system.

TL;DR: The form and validation results of APACHE II, a severity of disease classification system that uses a point score based upon initial values of 12 routine physiologic measurements, age, and previous health status, are presented.
Journal ArticleDOI

APACHE II-A Severity of Disease Classification System: Reply

TL;DR: The form and validation results of APACHE II, a severity of disease classification system, are presented, showing an increasing score was closely correlated with the subsequent risk of hospital death for 5815 intensive care admissions from 13 hospitals.
Journal ArticleDOI

A prediction rule to identify low-risk patients with community-acquired pneumonia

TL;DR: A prediction rule that stratifies patients into five classes with respect to the risk of death within 30 days accurately identifies the patients with community-acquired pneumonia who are at low risk for death and other adverse outcomes and may help physicians make more rational decisions about hospitalization for patients with pneumonia.
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