OBJECTIVE: Effective mechanical circulatory support (MCS) relies on cardiac function measures to guide titration. Left ventricular end diastolic pressure (LVEDP) is a useful measure that is indirectly estimated using pulmonary artery catheters (PACs). PACs require additional intervention and provide intermittent and unreliable estimations. MCS device signals can estimate LVEDP but are prone to inter-device variability and require rigorous specialized characterization. We present a scalable and implementable approach to calculate LVEDP continuously using device signals. METHODS: LVEDP was calculated from MCS device measured aortic pressure and motor current, which approximates the pressure head between the aorta and left ventricle. This motor current-pressure head relationship is device-specific but approximated using existing flow calibration and assumed physiologic relationships. Performance was evaluated with comparison from direct measurement of LVEDP in a series of acute animal models. RESULTS: LVEDP measures (n = 178,279) from 18 animals had good correlation (r = 0.84) and calibration (Bland-Altman limits of agreement -7.77 to 7.63 mmHg; mean bias -0.07 ± 0.02 mmHg). The total mean error prediction interval was -3.42 to 3.32 mmHg and RMS error was 3.85 mmHg. CONCLUSION: LVEDP can be continuously calculated using device signals without specialized characterization. Calculated LVEDP values improved upon PAC estimations and were found using a scalable and manufacturer-accessible method. SIGNIFICANCE: This method improves upon existing LVEDP measures without the need for rigorous characterization, external calibration, or additional intervention; this allows widescale deployment of continuous LVEDP measurement for patients on MCS and demonstrates key considerations necessary to translate research-grade technologies.
OBJECTIVE: Effective mechanical circulatory support (MCS) relies on cardiac function measures to guide titration. Left ventricular end diastolic pressure (LVEDP) is a useful measure that is indirectly estimated using pulmonary artery catheters (PACs). PACs require additional intervention and provide intermittent and unreliable estimations. MCS device signals can estimate LVEDP but are prone to inter-device variability and require rigorous specialized characterization. We present a scalable and implementable approach to calculate LVEDP continuously using device signals. METHODS: LVEDP was calculated from MCS device measured aortic pressure and motor current, which approximates the pressure head between the aorta and left ventricle. This motor current-pressure head relationship is device-specific but approximated using existing flow calibration and assumed physiologic relationships. Performance was evaluated with comparison from direct measurement of LVEDP in a series of acute animal models. RESULTS: LVEDP measures (n = 178,279) from 18 animals had good correlation (r = 0.84) and calibration (Bland-Altman limits of agreement -7.77 to 7.63 mmHg; mean bias -0.07 ± 0.02 mmHg). The total mean error prediction interval was -3.42 to 3.32 mmHg and RMS error was 3.85 mmHg. CONCLUSION: LVEDP can be continuously calculated using device signals without specialized characterization. Calculated LVEDP values improved upon PAC estimations and were found using a scalable and manufacturer-accessible method. SIGNIFICANCE: This method improves upon existing LVEDP measures without the need for rigorous characterization, external calibration, or additional intervention; this allows widescale deployment of continuous LVEDP measurement for patients on MCS and demonstrates key considerations necessary to translate research-grade technologies.
Authors: Francesco Moscato; Maurizio Arabia; Francesco M Colacino; Phornphop Naiyanetr; Guido A Danieli; Heinrich Schima Journal: Artif Organs Date: 2010-07-15 Impact factor: 3.094
Authors: Brian Y Chang; Zhengyang Zhang; Steven P Keller; Elazer R Edelman; Kimberly Feng; Noam Josephy Journal: Intensive Care Med Exp Date: 2021-12-20