Predicting acute pancreatitis without imaging

A novel prediction model using eight parameters may be effective at diagnosing acute pancreatitis without imaging, according to a study published in JAMA Network Open.

In the multicenter diagnostic study, researchers enrolled 349 patients who visited the emergency department with elevated serum lipase levels. The researchers assigned scores to the study participants based on their initial serum lipase levels, number of prior acute pancreatitis episodes, abdominal pain characteristics and medical history.

They found that nearly half of the patients had a final diagnosis of acute pancreatitis. The prediction model demonstrated effective discriminatory accuracy. At a diagnostic cutoff of at least six points, the model achieved a sensitivity of 81.5%, specificity of 85.9%, positive predictive value of 82.6%, and negative predictive value of 85.1% when diagnosing acute pancreatitis.

The researchers concluded that the novel prediction model may obviate the need for potentially unnecessary confirmatory diagnostic imaging with computed tomography or magnetic resonance imaging in this patient population.

Read more: JAMA Network Open

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