Abstract
Although many closed-loop drug delivery systems have been proposed for automatic regulation of blood pressure with sodium nitroprusside (SNP) [1-11], the only commercially available device is the IVAC TITRATOR™ System [12]. The TITRATOR System contains a self-tuning, nonlinear proportional-plus-integral-plus-derivative (PID) regulator. It continuously estimates and adjusts to patient sensitivity, baseline pressure, and control horizon. To provide increased patient safety, it has an integrated supervisor that constrains estimation, limits SNP infusion rates, responds aggressively to rapidly changing pressures, and rejects artifactual pressure measurements. The current FDA approved indications for use of the TITRATOR System are limited to the postoperative control of hypertension following cardiovascular surgery. Recent enhancements have been made to the system’s control algorithm in an attempt to widen the range of applications. The objective of this study was to determine, using an animal model, the performance of the TITRATOR System’s enhanced algorithm in inducing and maintaining deliberate hypotension during various challenges to blood pressure homeostasis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
JB Slate, “Model-Based Design of a Controller for Infusing Sodium Nitroprusside During Post Surgical Hypertension”, PhD dissertation, Dept of Electrical Engineering, U. Wisconsin- Madison, 1980
AJ Koivo, “Microprocessor-Based Controller for Pharmacodynamical Applications’, IEEE Trans Auto Control, Vol AC-26, pp 1208–1213, 1981
JM Arnsparger, BC Mclnnis, JR Glover, and NA Norman, “Adaptive Control of Blood Pressure”, IEEE Trans Biomed Eng, Vol BME-30, pp 168–176, 1983
LJ Meline, DR Westenskow, NL Pace, and MN Bodily, “Computer Controlled Regulation of Sodium Nitroprusside Infusion”, Anesth Analg, Vol 64, pp 38–42, 1985
KS Stern, HJ Chizek, BK Walker, PS Krishnaprasad, PJ Dauchot, and PG Katona, “The Self-Tuning Controller: Comparison with Human Perfromance in the Control of Arterial Pressure”, Ann Biomed Eng, Vol 13, pp 341–357, 1985
H Kaufman, R Roy, and X Xu, “Model Reference Adaptive Control of Drug Infusion Rate”, Automatica, Vol 20, pp 205–209, 1984
WG He, H Kaufman, and R Roy, “Multiple-Model Adaptive Control Procedure for Blood Pressure Control”, IEEE Trans Biomed Eng, Vol BME-33, pp 10–19, 1986
JF Martin, AM Schneider, and NT Smith, “Multiple-Model Adaptive Control of Blood Pressure Using Sodium Nitroprusside’,IEEE Trans Biomed Eng, Vol BME-34, pp 603–611, 1987
GI Voss, PG Katona, and HJ Chizek, “Adaptive Multivariable Drug Delivery Control of Arterial Pressure and Cardiac Output in Anesthetized Dogs”,IEEE Trans Biomed Eng, Vol BME-34, pp 617–6236, 1987
JS Packer, DG Mason, JF Cade, SM McKinley, ‘An Adaptive Controller for Closed-Loop Management of Blood Pressure in Seriously 111 Patents’, IEEE Trans Biomed Eng, Vol BME-34, pp 612–616, 1987
GA Pajunen, M Steinmetz, and R Shankar, “Model-Reference Adaptive Control with Contraints for Postoperative Blood Pressure Management-, IEEE Trans Biomed Eng, Vol BME-37, pp 679–687, 1990
DM Cosgrove, JH Petre, JL Waller, JV Roth, C Shepherd, and LH Cohn, “Automated Control of Postoperative Hypertension: A Prospective Randomized Muiticenter Study’, Ann Thorac Surg, Vol 47, pp 678–683, 1989
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1992 Springer-Verlag Tokyo
About this paper
Cite this paper
Smith, N.T., Martin, J.F., Quinn, M.L., Scanlon, T.S., Voss, G.I. (1992). Performance Evaluation of a Closed-Loop Sodium Nitroprusside Delivery Device during Hypotensive Anesthesia in Mongrel Dogs. In: Ikeda, K., Doi, M., Kazama, T., Sato, K., Oyama, T. (eds) Computing and Monitoring in Anesthesia and Intensive Care. Springer, Tokyo. https://doi.org/10.1007/978-4-431-68201-1_39
Download citation
DOI: https://doi.org/10.1007/978-4-431-68201-1_39
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-68203-5
Online ISBN: 978-4-431-68201-1
eBook Packages: Springer Book Archive