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Related Experiment Video

Updated: Jun 3, 2026

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

Device features for managing patients with heart failure.

Niraj Varma¹, Bruce Wilkoff

¹Cardiac Pacing and Electrophysiology, Department of Cardiovascular Medicine, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA. varman@ccf.org

Heart Failure Clinics

|March 29, 2011

Summary

Remote monitoring of implanted heart failure devices can help detect early changes, enabling prompt treatment. This proactive approach aims to reduce mortality and improve outcomes for high-risk patients.

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Workflow and Framework for Collecting and Implementing Point-of-Care Ultrasound Data in the Management of Heart Failure Patients

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Last Updated: Jun 3, 2026

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

Workflow and Framework for Collecting and Implementing Point-of-Care Ultrasound Data in the Management of Heart Failure Patients

Workflow and Framework for Collecting and Implementing Point-of-Care Ultrasound Data in the Management of Heart Failure Patients

Published on: July 12, 2024

Area of Science:

Cardiology
Biomedical Engineering
Health Informatics

Background:

Implantable devices enhance survival in heart failure patients but require precise management.
Heart failure is a dynamic condition necessitating adaptive treatment strategies.
Acute decompensation events in heart failure increase mortality due to converging physiological processes.

Purpose of the Study:

To evaluate the role of remote monitoring in managing heart failure patients with implanted devices.
To assess the potential of early detection of deviations for pre-emptive treatment.
To explore how technology can facilitate the management of large heart failure patient cohorts.

Main Methods:

Utilizing remote monitoring technology, as exemplified by the TRUST Trial.
Tracking key parameters including rhythm, device function, and hemodynamics.
Prompt notification of deviations from established baselines, even in asymptomatic patients.

Main Results:

Remote monitoring enables continuous tracking of vital parameters in heart failure patients.
Early identification of deviations, including asymptomatic changes, is facilitated.
Potential for improved patient management and pre-emptive interventions.

Conclusions:

Remote monitoring of implanted devices offers a promising strategy for managing heart failure.
Proactive management through early detection can mitigate risks associated with acute decompensation.
This approach may significantly improve long-term outcomes for high-risk heart failure populations.