# Non-Invasive Venous waveform Analysis (NIVA) for Monitoring Volume Status in Heart Failure Patients

> **NIH NIH R01** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2024 · $392,932

## Abstract

PROJECT SUMMARY
The primary focus of this research proposal is the refinement and advanced optimization of the
Non-Invasive Venous waveform Analysis for Heart Failure (NIVAHF) device, building upon the
foundational achievements made under R01HL148244. This device represents a pioneering
stride in the field of cardiology, offering the potential for accurate, non-invasive monitoring of
volume status, which is paramount for heart failure patients. The advancements made in recent
years have rendered a significant shift in our understanding of venous waveforms, leading to the
development of this revolutionary monitoring tool--NIVAHF. This tool, at its core, employs an AI
neural network algorithm to generate a NIVA Score, a pulmonary capillary wedge pressure
(PCWP) equivalent value. This renewal looks to investigate and confront three major limitations
found with venous waveform analysis in heart failure patients: tricuspid regurgitation (TR), those
having undergone orthotopic heart transplantation (OHT), and those supported by a left
ventricular assist device (LVAD). The prevalence of TR in heart failure patients, due to
hemodynamic changes, makes it an essential marker of disease severity. Heart transplant
recipients are particularly vulnerable, requiring continuous monitoring to detect early signs of
graft dysfunction or rejection. Similarly, for LVAD-supported patients, consistent PCWP
monitoring becomes a cornerstone for optimal care, as it helps in reducing complications and
enhancing overall health outcomes. To address the complex challenges associated with venous
waveform analysis, our research advances a multifaceted approach. Initially, we will delve into
characterizing the intricate relationship between TR severity and the NIVA Score by harnessing
an expansive database and analysis plan. This endeavor aims to recalibrate the device's
precision for patients exhibiting different stages of TR. Concurrently, understanding the criticality
of post-transplant surveillance, we will lay the groundwork for an OHT specific NIVAHF algorithm.
This innovation will be pivotal in the early detection of graft anomalies, potentially amplifying
survival rates and uplifting health trajectories for OHT beneficiaries. Lastly, as LVADs,
especially the HeartMate 3, become indispensable in heart failure management, our focus
sharpens on crafting an AI-driven neural network algorithm tailored for HM3 LVAD patients. The
culmination of these targeted efforts will be to furnish a dependable, non-invasive PCWP
monitoring device with NIVAHF to these vulnerable heart failure patients.

## Key facts

- **NIH application ID:** 10981403
- **Project number:** 2R01HL148244-06
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Bret D. Alvis
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $392,932
- **Award type:** 2
- **Project period:** 2019-08-01 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10981403

## Citation

> US National Institutes of Health, RePORTER application 10981403, Non-Invasive Venous waveform Analysis (NIVA) for Monitoring Volume Status in Heart Failure Patients (2R01HL148244-06). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10981403. Licensed CC0.

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