Tube-load model: A clinically applicable pulse contour analysis method for estimation of cardiac stroke volume. (June 2021)

• Record Type: Journal Article
• Authors: Smith, Rachel; Murphy, Liam; Pretty, Christopher G.; Desaive, Thomas; Shaw, Geoffrey M.; Chase, J. Geoffrey
• Is Part Of: Computer methods and programs in biomedicine. Volume 204(2021)
• Publication Date: 2021-06
• Subjects: Pulse contour analysis -- Tube-load model -- Stroke volume -- Hemodynamic monitoring -- Intensive care -- Arterial wave reflection; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2021.106062
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Dynamically identified tube-load model for pulse contour analysis, accounting for arterial wave reflection. Validation during clinically relevant recruitment manoeuvre, fluid administration, and induced septic shock interventions. Tube-load model provides physiologically realistic central pressure and flow waveform estimates, and reasonable cardiac stroke volume estimation. Abstract: Background and Objectives: Accurate, reproducible, and reliable real-time clinical measurement of stroke volume (SV) is challenging. To accurately estimate arterial mechanics and SV by pulse contour analysis, accounting for wave reflection, such as by a tube-load model, is potentially important. This study tests for the first time whether a dynamically identified tube-load model, given a single peripheral arterial input signal and pulse transit time (PTT), provides accurate SV estimates during hemodynamic instability. Methods: The model is tested for 5 pigs during hemodynamic interventions, using either an aortic flow probe or admittance catheter for a validation SV measure. Performance is assessed using Bland-Altman and polar plot analysis for a series of long-term state-change and short-term dynamic events. Results: The overall median bias and limits of agreement (2.5th, 97.5th percentile) from Bland-Altman analysis were -10% [-49, 36], and -1% [-28, 20] for state-change and dynamic events, respectively. The angular limit of agreement (maximum of 2.5th, 97.5th percentile) from polar-plot analysis for state-change and dynamic interventions was 35.6 ∘, and 35.2 ∘, respectively. Conclusion: SV estimation agreement and trending performance was reasonable given the severity of the interventions. This simple yet robust method has potential to track SV within acceptable limits during hemodynamic instability in critically ill patients, provided a sufficiently accurate PTT measure.