• Joseph Rinehart, Michael Ma, Michael-David Calderon, and Maxime Cannesson.
• Department of Anesthesiology & Perioperative Care, University of California Irvine, 101 The City Dr. South, Orange, CA, 92868, USA. jrinehar@uci.edu.
• J Clin Monit Comput. 2018 Feb 1; 32 (1): 5-11.

AbstractBlood pressure management is a central concern in critical care patients. For a variety of reasons, titration of vasopressor infusions may be an ideal use-case for computer assistance. Using our previous experience gained in the bench-to-bedside development of a computer-assisted fluid management system, we have developed a novel controller for this purpose. The aim of this preliminary study was to assess the feasibility of using this controller in simulated patients to maintain a target blood pressure in both stable and variable blood-pressure scenarios. We tested the controller in two sets of simulation scenarios: one with stable underlying blood pressure and a second with variable underlying blood pressure. In addition, in the variable phase of the study, we tested infusion-line delays of 8-60 s. The primary outcome for both testing conditions (stable and variable) was % case time in target range. We determined a priori that acceptable performance on the first phase of the protocol would require greater than 95% case-time in-target given the simple nature of the protocol, and for the second phase of the study 80% or greater given the erratic nature of the blood pressure changes taking place. 250 distinct cases for each simulation condition, both managed and unmanaged, were run over 4 days. In the stable hemodynamic conditions, the unmanaged group had an MAP of 57.5 ± 4.6 mmHg and spent only 5.6% of case time in-target. The managed group had an MAP of 70.3 ± 2.6 and spent a total of 99.5% of case time in-target (p < 0.00001 for both comparisons between groups). In the variable hemodynamic conditions, the unmanaged group had an MAP of 53.1 ± 5.0 mmHg and spent 0% of case time in-target. The managed group had an MAP of 70.5 ± 3.2 mmHg (p < 0.00001 compared to unmanaged group) and spent 88.6% of case time in-target (p < 0.00001 compared to unmanaged group), with 6.4% of case time over and 5.1% of case time under target. Increasing infusion lag increased coefficient of variation by about 10% per 15 s of lag (p = 0.001). This study demonstrated that this novel controller for vasopressor administration is able to main a target mean arterial pressure in a simulated physiologic model in the face of random disturbances and infusion-line lag.

27 keywords...

hide…