AI Platform Supports Noninvasive Remote Hemodynamic Monitoring in Heart Failure

7 million people in the U.S. Clinicians often lose visibility into hemodynamic deterioration once patients leave the hospital, and invasive catheterization is performed in only a small fraction of cases. Noninvasive options are typically limited to in-hospital imaging or implantables reserved for the highest-risk patients. A new AI-based platform now offers catheterization-comparable hemodynamic assessment using consumer wearables under physician supervision to extend monitoring beyond the hospital.

Coredio’s (Santa Clara, CA, USA) Cardiac Performance Simulation Engine (CPSE) is a software-as-a-medical-device platform (SaMD) dedicated to heart failure hemodynamic assessment. The software-only, device-agnostic system is designed for use with consumer smartwatches and standard blood pressure cuffs in clinical and home settings under physician supervision. CPSE is intended to support clinician assessment by bringing advanced hemodynamic evaluation to where patients spend most of their time.

The platform pairs a physics-based digital twin of the patient’s cardiovascular system with machine-learning models trained on clinical data. After an initial personalization step, patients collect signals via a smartwatch and blood pressure cuff to generate an on-demand indication of hemodynamic status for clinician review. CPSE’s proprietary algorithms are designed to identify abnormal status across four key parameters central to cardiology decision-making: left ventricular end-diastolic pressure, central venous pressure, systemic vascular resistance, and cardiac index.

Coredio reported that the U.S. Food and Drug Administration (FDA) has granted CPSE Breakthrough Device Designation and accepted the platform into the agency’s Total Product Life Cycle Advisory Program (TAP). The company noted it is on an accelerated, priority path toward a future 510(k) submission. By leveraging consumer wearables patients already own, CPSE is designed to help close the gap between hospital-based measurements and outpatient insight. The approach aims to provide a more holistic view of left- and right-sided heart failure status without invasive procedures or additional clinic visits.

“Heart failure management has long been limited by the gap between what we can measure in the hospital and what we can reliably understand once patients return home. Coredio’s approach, using wearable-derived signals and physics-informed AI to estimate hemodynamic status noninvasively, has the potential to give clinicians a more holistic view of patient cardiac function and enable earlier intervention,” said Dr. Jagmeet P. Singh, MD, PhD, Mass General Brigham.

“Heart failure management has long been limited by the gap between what we can assess invasively or with imaging tools and what we can see at home. Coredio’s approach, extracting catheterization-comparable hemodynamic data from consumer wearables using physics-based AI, has the potential to close that gap and give clinicians the visibility they need to intervene earlier and make more informed decisions for heart failure patients,” said Dr. Jennifer Monti, Cardiologist, SSM Health.

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