Decision tool for the early diagnosis of trauma patient hypovolemia.
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Date
2008-06-05
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Abstract
We present a classifier for use as a decision assist tool to identify a hypovolemic state in trauma patients during helicopter transport to a hospital when reliable acquisition of vital sign data may be difficult The decision tool uses basic vital sign variables as input into linear classifiers which are then combined into an ensemble classifier The classifier identifies hypovolemic patients with an area under a receiver operating characteristic curve AUC of 0 76 standard deviation 0 05 for 100 randomly reselected patient subsets The ensemble classifier is robust classification performance degrades only slowly as variables are dropped and the ensemble structure does not require identification of a set of variables for use as best feature inputs into the classifier The ensemble classifier consistently outperforms best features based linear classifiers the classification AUC is greater and the standard deviation is smaller pUnder0 05 The simple computational requirements of ensemble classifiers will permit them to function in small fieldable devices for continuous monitoring of trauma patients