Real-Time, Minimally Invasive, Beat-to-Beat Estimation of End-Systolic Volume Using a Modified End-Systolic Pressure-Volume Relation. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Davidson, Shaun M.; Pretty, Chris; Kamoi, Shun; Balmer, Joel; Desaive, Thomas; Geoffrey Chase, J.
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 5456
• Page End: 5461
• Publication Date: 2017-07
• Subjects: Biomedical Systems -- Medical Applications -- Biomedical Control -- Medical Systems -- Least-Squares Estimation; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.1082
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Intensive care management of cardiovascular disease and dysfunction, a major and growing issue, would benefit from improved synthesis of continuously monitored, information rich catheter waveforms into clear, relevant cardiac metrics. Volume measurements are rarely taken in intensive care, but advances have been made in approximating cardiac stroke volume using pressure measurements. This paper proposes a method for the minimally invasive, real-time, beat-to-beat estimation of end-systolic volume, with the goal of providing further insight into cardiac volume behavior and access to important metrics such as cardiac preload. This method relies on a modified end-systolic pressure-volume relation, aortic pressure and heart rate data and a brief echocardiography calibration. The method was validated across 11 pigs and 2 protocols, encompassing the progression of sepsis and a variety clinical procedures employed in the management of sepsis. The method demonstrated consistently strong correlation coefficients, with a mean of R = 0.82, and low estimation error, with a mean absolute percentage error of 13.3%. This method thus allows effective estimation of end-systolic volume, providing a more complete picture of cardiac behavior in an intensive care environment in which volume measurements are rarely taken. As such, the method has the potential to benefit clinical decision making and management of cardiovascular disease and dysfunction.