DocumentCode :
3521245
Title :
A predictive model for the anticoagulant bivalirudin administered to cardiac surgical patients
Author :
Qi Zhao ; Edrich, Thomas ; Paschalidis, Ioannis C.
Author_Institution :
Div. of Syst. Eng., Boston Univ., Boston, MA, USA
fYear :
2013
fDate :
10-13 Dec. 2013
Firstpage :
121
Lastpage :
126
Abstract :
Bivalirudin is used in patients with heparin-induced thrombocytopenia and is a direct thrombin inhibitor. Since it is a rarely used drug, clinical experience with its dosing is sparse. We develop a model that predicts the effect of bivalirudin, measured by the Partial Thromboplastin Time (PTT), based on its past fusion rates. We learn population-wide model parameters by solving a nonlinear optimization problem that uses a training set of patient data. More interestingly, we devise an adaptive algorithm based on the extended Kalman filter that can adapt model parameters to individual patients. The latter adaptive model emerges as the most promising as it reduces both the mean error and, drastically, the per-patient error variance. The model accuracy we demonstrate on actual patient measurements is sufficient to be useful in guiding optimal therapy.
Keywords :
Kalman filters; blood; drugs; haemorheology; nonlinear filters; nonlinear programming; surgery; PTT; adaptive algorithm; anticoagulant bivalirudin; bivalirudin effect prediction model; cardiac surgical patients; clinical experience; direct thrombin inhibitor; drug dose; extended Kalman filter; fusion rate; heparin-induced thrombocytopenia patients; nonlinear optimization problem; optimal therapy; partial thromboplastin time; patient data; patient measurement; per-patient error variance; population-wide model parameters; predictive model; rarely used drug; Adaptation models; Coagulation; Mathematical model; Prediction algorithms; Predictive models; Time measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
ISSN :
0743-1546
Print_ISBN :
978-1-4673-5714-2
Type :
conf
DOI :
10.1109/CDC.2013.6759869
Filename :
6759869
Link To Document :
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