Diagnosis of hemorrhage in a prehospital trauma population using linear and nonlinear multiparameter analysis of vital signs.
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2007-11-16
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Abstract
In this study we analyzed a dataset of time series vital signs data collected by standard Propaq travel monitor during helicopter transport of 898 civilian trauma casualties from the scene of injury to a receiving trauma center The goals of the analysis are two fold First to determine which combination of the automatically collected and qualified vital signs provides the best discrimination between casualties with and without major hemorrhage Second to determine whether nonlinear classifiers provide improved discrimination over simpler linear classifiers Major hemorrhage is defined by the presence of injuries consistent with hemorrhage in casualties who received one or more units of blood We randomly selected a subset of the casualties to train and test the classifiers with multiple combinations of the vital signs variables and used the area under the receiver operating characteristic curve ROC AUC as a decision metric Based on the results of 100 simulations we observe that i the best two features obtained are systolic blood pressure and heart rate mean AUC 0 75 from a linear classifier and ii the use of nonlinear classifiers does not improve discrimination These results support earlier findings that the interaction of systolic blood pressure and heart rate is useful for the identification of trauma hemorrhage and that linear classifiers are adequate for many real world applications