This original research publication presents a new and innovative application of pharmacokinetic data analysis, usually applied to drug disposition, to the physiologic effects of parenteral intravenous fluid administration. In classical pharmacokinetic data analysis, a drug is administered, blood is sampled, and drug concentrations are measured over time. Pharmacokinetic models, usually mamillary with first-order kinetics, are fit to the measured drug concentrations using nonlinear least-squares regression. The data analysis estimates drug volumes and clearances that characterize the extent of drug distribution into body tissues and the rate of drug movement between tissues and removal from the body. Drs. Svensen and Hahn have examined the pharmacokinetics of the intravenous administration of Ringer's acetate, 6% dextran, and 7.5% NaCl using the dilution of three markers in blood, blood hemoglobin, blood water, and plasma albumin, analogous to the measurement of drug concentrations. The authors developed one- and two-compartment mamillary models and then used nonlinear regression to characterize the blood marker dilution versus time, relative to the administered dose of intravenous fluid. The authors report that the volume of body fluid space expanded by the intravenous fluid was greatest for Ringers (change of 5.9 l), followed by dextran (change of 2.6 l), and was least with hypertonic saline (change of 1.2 l). The authors' data analysis approaches will require more rigorous evaluation; however, the fundamental concept that they suggest may provide a new clinical research tool to understand how intravenous fluids used in anesthetic practice affect the body. The concepts presented in this article could be used to provide better quantitation of the effects of different intravenous fluids in different patient populations or clinical situations and also allow for more rational design of intravenous fluid administration paradigms.
Donald R. Stanski, M.D.
Professor and Chair; Department of Anesthesia; Stanford University School of Medicine; Stanford, California 94305