title: On the use of multivariable piecewise-linear models for predicting human response to anesthesia.
abstract: The standard modeling paradigm used to describe the relationship between input anesthetic agents and output patient endpoint variables are single-input single-output pharmacokinetic-pharmacodynamic (PK-PD) compartment models. In this paper, we propose the use of multivariable piecewise-linear models to describe the relations between inputs that include anesthesia, surgical stimuli and disturbances to a variety of patient output variables. Subspace identification methods are applied to clinical data to construct the models. A comparison of predicted and measured responses is completed, which includes predictions from PK-PD models, and piecewise-linear time-invariant models.
authors.affiliation: Department of Mechanical and Industrial Engineering, University of Illinois, Urbana, IL 61801, USA.
authors.forename: Hui-Hing
authors.initials: HH
authors.lastname: Lin
authors.forename: Carolyn L
authors.initials: CL
authors.lastname: Beck
authors.forename: Marc J
authors.initials: MJ
authors.lastname: Bloom
mesh_terms: D000328:Adult; D000465:Algorithms; D000758:Anesthesia / Q000379:methods*; D000777:Anesthetics / Q000008:administration & dosage* / Q000097:blood / Q000494:pharmacology*; D003198:Computer Simulation; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000187:drug effects*; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D008954:Models, Biological; D015999:Multivariate Analysis; D010865:Pilot Projects
chemical_list: D000777:Anesthetics