Author: Rau Cheng-Shyuan Wu Shao-Chun Chien Peng-Chen Kuo Pao-Jen Chen Yi-Chun Hsieh Hsiao-Yun Hsieh Ching-Hua Liu Hang-Tsung
Publisher: MDPI
E-ISSN: 1660-4601|15|2|277-277
ISSN: 1660-4601
Source: International Journal of Environmental Research and Public Health, Vol.15, Iss.2, 2018-02, pp. : 277-277
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Abstract
Background: In trauma patients, pancreatic injury is rare; however, if undiagnosed, it is associated with high morbidity and mortality rates. Few predictive models are available for the identification of pancreatic injury in trauma patients with elevated serum pancreatic enzymes. In this study, we aimed to construct a model for predicting pancreatic injury using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry in a Level I trauma center. Methods: A total of 991 patients with elevated serum levels of amylase (>137 U/L) or lipase (>51 U/L), including 46 patients with pancreatic injury and 865 without pancreatic injury between January 2009 and December 2016, were allocated in a ratio of 7:3 to training (
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