Title of article :
A New Approach towards Minimizing the Risk of Misdosing Warfarin Initiation Doses
Author/Authors :
Sharabiani, Ashkan Department of Mechanical and Industrial Engineering - University of Illinois at Chicago - Chicago, USA , Nutescu, Edith A Department of Pharmacy Systems Outcomes and Policy and Center for Pharmacoepidemiology and Pharmacoeconomic Research - University of Illinois at Chicago - Chicago, USA , Galanter, William L Department of Pharmacy Systems Outcomes and Policy and Center for Pharmacoepidemiology and Pharmacoeconomic Research - University of Illinois at Chicago - Chicago, USA , Darabi, Houshang Department of Mechanical and Industrial Engineering - University of Illinois at Chicago - Chicago, USA
Abstract :
It is a challenge to be able to prescribe the optimal initial dose of warfarin.Tere have been many studies focused on an efcient strategy to determine the optimal initial dose. Numerous clinical, genetic, and environmental factors afect the warfarin dose response. In
practice, it is common that the initial warfarin dose is substantially diferent from the stable maintenance dose, which may increase
the risk of bleeding or thrombosis prior to achieving the stable maintenance dose. In order to minimize the risk of misdosing, despite
popular warfarin dose prediction models in the literature which create dose predictions solely based on patients’ attributes, we have
taken physicians’ opinions towards the initial dose into consideration. Te initial doses selected by clinicians, along with other
standard clinical factors, are used to determine an estimate of the diference between the initial dose and estimated maintenance
dose using shrinkage methods. Te selected shrinkage method was LASSO (Least Absolute Shrinkage and Selection Operator). Te
estimated maintenance dose was more accurate than the original initial dose, the dose predicted by a linear model without involving
the clinicians initial dose, and the values predicted by the most commonly used model in the literature, the Gage clinical model.
Keywords :
Risk , LASSO , VKORC1
Journal title :
Computational and Mathematical Methods in Medicine