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Predicting the severity of acute pancreatitis

Santhi Swaroop Vege, MD
Section Editor
David C Whitcomb, MD, PhD
Deputy Editor
Shilpa Grover, MD, MPH


Approximately 15 to 25 percent of all patients with acute pancreatitis (AP) develop severe AP. Between 1988 and 2003, mortality from acute pancreatitis decreased from 12 percent to 2 percent, according to a large epidemiologic study from the United States [1]. However, mortality rates remain much higher in subgroups of patients with severe disease. The ability to predict its severity can help identify patients at increased risk for morbidity and mortality, thereby assisting in appropriate early triage to intensive care units and selection of patients for specific interventions.

This topic review will summarize methods for predicting the severity of AP. The clinical manifestations, diagnosis, and treatment of AP are discussed separately. (See "Clinical manifestations and diagnosis of acute pancreatitis" and "Management of acute pancreatitis".)


A multitude of predictive models have been developed to predict the severity of AP based upon clinical, laboratory, and radiologic risk factors, various severity grading systems, and serum markers [2]. Some of these can be performed on admission to assist in triage of patients, while others can only be obtained after the first 48 to 72 hours or later.

However, these predictive models have low specificity (ie, high false positive rates), which, when coupled with the low prevalence of severe AP (15 to 25 percent), results in low positive predictive values [3]. Future predictive models will need to incorporate additional factors (eg, biomarkers, genetic polymorphisms and mutations, and proteomic and metabolomic patterns) and methods of analyses [4].


The revised Atlanta classification system divides acute pancreatitis into two broad categories (table 1) [5,6]:


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