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Robust and adaptive anticoagulant control
Author(s) -
Avery Peter,
Clairon Quentin,
Henderson Robin,
James Taylor C.,
Wilson Emma
Publication year - 2020
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12403
Subject(s) - stability (learning theory) , focus (optics) , term (time) , mathematical optimization , matching (statistics) , computer science , control (management) , warfarin , mathematics , statistics , medicine , artificial intelligence , machine learning , physics , quantum mechanics , optics , cardiology , atrial fibrillation
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.