The cardiac output from blood pressure algorithms trial*

Abstract

Objective The value of different algorithms that estimate cardiac output (CO) by analysis of a peripheral arterial blood pressure (ABP) waveform has not been definitively identified. In this investigation, we developed a testing data set containing a large number of radial ABP waveform segments and contemporaneous reference CO by thermodilution measurements, collected in an intensive care unit (ICU) patient population during routine clinical operations. We employed this data set to evaluate a set of investigational algorithms, and to establish a public resource for the meaningful comparison of alternative CO-from-ABP algorithms. Design A retrospective comparative analysis of eight investigational CO-from-ABP algorithms using the Multiparameter Intelligent Monitoring in Intensive Care II database. Setting Mixed medical/surgical ICU of a university hospital. Patients A total of 120 cases. Interventions None. Measurements CO estimated by eight investigational CO-from-ABP algorithms, and COTD as a reference. Main Results All investigational methods were significantly better than mean arterial pressure (MAP) at estimating direction changes in COTD. Only the formula proposed by Liljestrand and Zander in 1928 was a significantly better quantitative estimator of COTD compared with MAP (95% limits-of-agreement with COTD: –1.76/+1.41 L/min versus –2.20/+1.82 L/min, respectively; p < 0.001, per the Kolmogorov-Smirnov test). The Liljestrand method was even more accurate when applied to the cleanest ABP waveforms. Other investigational algorithms were not significantly superior to MAP as quantitative estimators of CO. Conclusions Based on ABP data recorded during routine intensive care unit (ICU) operations, the Liljestrand and Zander method is a better estimator of COTD than MAP alone. Our attempts to fully replicate commercially-available methods were unsuccessful, and these methods could not be evaluated. However, the data set is publicly and freely available, and developers and vendors of CO-from-ABP algorithms are invited to test their methods using these data.

Importance of re-calibration time on pulse contour analysis agreement with thermodilution measurements of cardiac output: a retrospective analysis of intensive care unit patients

“…Concordance to assess the agreement in directional change obtained in this study agreed with previous studies (*80 %) [25]. However, CO differences from two methods that would be deemed to be concordant may not have the same clinical interpretation because concordance assesses only direction, not magnitude, of differences between the methods.…”

“…ABP waveform features including peak times, start and end points for systole, diastolic, systolic and mean blood pressures, and the systolic area were determined using the beat detector and feature extraction methods as reported in [25,30,31] with the Matlab (The Mathworks, Inc., Natick, MA) implementation provided by Sun at (http://www.phy sionet.org/physiotools/cardiac-output/) [32]. We used the three-element Windkessel model to convert the ABP waveform into a flow waveform, and the integral of flow during systole is then taken as the SV to obtain the pulse contour analysis cardiac output estimate (CO PCA ) using (1) [4].…”

“…MIMIC-II provides a diverse, clinically relevant group of patients [25,26]. Given the length of data and changing hemodynamic states during patient stays, we are able to perform analyses that describe performance in an uncontrolled environment.…”

“…ABP waveforms were obtained at 125 Hz using the M1006B pressure module connected to a Philips Component Monitoring System Intellivue MP-70 patient monitor (Philips Healthcare). Intermittent thermodilution measurements were made from a pulmonary artery catheter [25,26]. Paired data points refer to a thermodilution measurement matched with the preceding 1 min ABP waveform segment.…”

“…A comparison of pulse contour analysis CO estimates from ABP waveforms using an intensive care unit (ICU) patient population has been explored by using the publicly available Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database [25,26]. Pulse contour analyses that use the waveform characteristics of ABP or non-invasive plethysmographic data to estimate CO only require post-processing of such monitoring data.…”