OBJECTIVE: Tracking changes in hemodynamic congestion and the consequent proactive readjustment of treatment has shown efficacy in reducing hospitalizations for patients with heart failure (HF). However, the cost-prohibitive nature of these invasive sensing systems precludes their usage in the large patient population affected by HF. The objective of this research is to estimate the changes in pulmonary artery mean pressure (PAM) and pulmonary capillary wedge pressure (PCWP) following vasodilator infusion during right heart catheterization (RHC), using changes in simultaneously recorded wearable seismocardiogram (SCG) signals captured with a small wearable patch. METHODS: A total of 20 patients with HF (20% women, median age 55 (interquartile range (IQR), 44-64) years, ejection fraction 24 (IQR, 16-43)) were fitted with a wearable sensing patch and underwent RHC with vasodilator challenge. We divided the dataset randomly into a training-testing set (n = 15) and a separate validation set (n = 5). We developed globalized (population) regression models to estimate changes in PAM and PCWP from the changes in simultaneously recorded SCG. RESULTS: The regression model estimated both pressures with good accuracies: root-mean-square-error (RMSE) of 2.5 mmHg and R2 of 0.83 for estimating changes in PAM, and RMSE of 1.9 mmHg and R2 of 0.93 for estimating changes in PCWP for the training-testing set, and RMSE of 2.7 mmHg and R2 of 0.81 for estimating changes in PAM, and RMSE of 2.9 mmHg and R2 of 0.95 for estimating changes in PCWP for the validation set respectively. CONCLUSION: Changes in wearable SCG signals may be used to track acute changes in intracardiac hemodynamics in patients with HF. SIGNIFICANCE: This method holds promise in tracking longitudinal changes in hemodynamic congestion in hemodynamically-guided remote home monitoring and treatment for patients with HF.
OBJECTIVE: Tracking changes in hemodynamic congestion and the consequent proactive readjustment of treatment has shown efficacy in reducing hospitalizations for patients with heart failure (HF). However, the cost-prohibitive nature of these invasive sensing systems precludes their usage in the large patient population affected by HF. The objective of this research is to estimate the changes in pulmonary artery mean pressure (PAM) and pulmonary capillary wedge pressure (PCWP) following vasodilator infusion during right heart catheterization (RHC), using changes in simultaneously recorded wearable seismocardiogram (SCG) signals captured with a small wearable patch. METHODS: A total of 20 patients with HF (20% women, median age 55 (interquartile range (IQR), 44-64) years, ejection fraction 24 (IQR, 16-43)) were fitted with a wearable sensing patch and underwent RHC with vasodilator challenge. We divided the dataset randomly into a training-testing set (n = 15) and a separate validation set (n = 5). We developed globalized (population) regression models to estimate changes in PAM and PCWP from the changes in simultaneously recorded SCG. RESULTS: The regression model estimated both pressures with good accuracies: root-mean-square-error (RMSE) of 2.5 mmHg and R2 of 0.83 for estimating changes in PAM, and RMSE of 1.9 mmHg and R2 of 0.93 for estimating changes in PCWP for the training-testing set, and RMSE of 2.7 mmHg and R2 of 0.81 for estimating changes in PAM, and RMSE of 2.9 mmHg and R2 of 0.95 for estimating changes in PCWP for the validation set respectively. CONCLUSION: Changes in wearable SCG signals may be used to track acute changes in intracardiac hemodynamics in patients with HF. SIGNIFICANCE: This method holds promise in tracking longitudinal changes in hemodynamic congestion in hemodynamically-guided remote home monitoring and treatment for patients with HF.
Authors: Paul Sorajja; Barry A Borlaug; Vasiliki V Dimas; James C Fang; Paul R Forfia; Michael M Givertz; Navin K Kapur; Morton J Kern; Srihari S Naidu Journal: Catheter Cardiovasc Interv Date: 2017-05-10 Impact factor: 2.692
Authors: Offer Amir; Tuvia Ben-Gal; Jean Marc Weinstein; Jorge Schliamser; Daniel Burkhoff; Aharon Abbo; William T Abraham Journal: Int J Cardiol Date: 2017-03-03 Impact factor: 4.164
Authors: Michael K Ong; Patrick S Romano; Sarah Edgington; Harriet U Aronow; Andrew D Auerbach; Jeanne T Black; Teresa De Marco; Jose J Escarce; Lorraine S Evangelista; Barbara Hanna; Theodore G Ganiats; Barry H Greenberg; Sheldon Greenfield; Sherrie H Kaplan; Asher Kimchi; Honghu Liu; Dawn Lombardo; Carol M Mangione; Bahman Sadeghi; Banafsheh Sadeghi; Majid Sarrafzadeh; Kathleen Tong; Gregg C Fonarow Journal: JAMA Intern Med Date: 2016-03 Impact factor: 21.873
Authors: William T Abraham; Lynne W Stevenson; Robert C Bourge; Jo Ann Lindenfeld; Jordan G Bauman; Philip B Adamson Journal: Lancet Date: 2015-11-09 Impact factor: 79.321
Authors: David M Shavelle; Akshay S Desai; William T Abraham; Robert C Bourge; Nirav Raval; Lisa D Rathman; J Thomas Heywood; Rita A Jermyn; Jamie Pelzel; Orvar T Jonsson; Maria Rosa Costanzo; John D Henderson; Marie-Elena Brett; Philip B Adamson; Lynne W Stevenson Journal: Circ Heart Fail Date: 2020-08-06 Impact factor: 8.790