| Summary: | <h4>Background</h4>Acute pancreatitis (AP) is associated with high complications. Early, reliable prediction of mortality may improve patient management.<h4>Methods</h4>We retrospectively reviewed medical records of 1,599 patients with AP treated at a single large hospital in southwest China. Models to predict mortality were derived from a subset of 1,062 patients (development dataset), and the models were then validated in the remaining 537 patients (validation dataset). Independent risk factors and prediction models for mortality were identified using logistic regression.<h4>Results</h4>A total of 33 patients in the development dataset and 13 in the validation dataset died during hospitalization. Independent risk factors for mortality were found to be plasma urea levels, glucose levels and platelet counts at admission; as well as peak urea levels, leukocyte counts and use of invasive ventilation during hospitalization. Based on the development dataset, a mortality prediction model based only on urea level at admission gave an area under the curve (AUC) of 0.81, which did not significantly improve by incorporating glucose level or platelet count at admission. Significantly better was a model taking into account three in-hospital parameters: peak urea level, leukocyte count and use of invasive ventilation (AUC 0.97).<h4>Conclusions</h4>While mortality of AP patients can be predicted reasonably well based only on urea values at admission, predictions are more reliable when they take into account in-hospital data on peak urea level, leukocyte count and use of invasive ventilation.
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