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Does a proportional-integral-plus control method improve INR tracking stability compared to a naive deadbeat approach in patients on long-term warfarin?
Does a proportional-integral-plus control method improve INR tracking stability compared to a naive deadbeat approach in patients on long-term warfarin?
A proportional-integral-plus control theory approach provides more robust and stable warfarin dosing recommendations compared to naive deadbeat methods in simulated patient models.
Summary We consider a control theory approach to adaptive dose allocation of anticoagulants, based on an analysis of records of 152 patients on long-term warfarin treatment. We consider a selection of statistical models for the relationship between the dose of drug and subsequent blood clotting speed, measured through the international normalized ratio. Our main focus is on subsequent use of the model in guiding the choice of the next dose adaptively as patient-specific information accrues. We compare a naive long-term approach with a proportional-integral-plus method, with parameters estimated by either linear quadratic optimization or by stochastic resource allocation. We demonstrate advantages of the control approaches in comparison with a naive approach in simulations and through calculation of robust stability margins for the observed data.
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Avery et al. (2020) studied this question.
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