Congestive heart failure (CHF) is the most common cause of hospital admissions worldwide, and costs an estimated $40 billion annually in the US alone. Patients are most often hospitalized for pulmonary congestion and shortness of breath due to volume overload, but an estimated 50-80% of these hospitalizations could be prevented by optimizing medical treatment before significant symptoms arise. There remains a significant unmet need for affordable, non-invasive, real-time volume status monitoring in the outpatient CHF setting. This study will focus on development of a Non-Invasive Venous waveform Analysis (NIVA) device for hemodynamic volume assessment. The NIVA uses venous waveform analysis, rather than the commonly used pressure analysis to detect changes in venous compliance due to changes in volume. The hypothesis of this proposal is that NIVA will provide a reliable, non-invasive, quantitative measure of intravascular volume status in outpatients with CHF.
The first aim of the study is to characterize the effect of hemodynamic and pharmacologic perturbations on NIVA signal using a porcine model. This information will provide data for optimizing the NIVA algorithm and mitigating potential confounding variables such as vasoactive drug use. We anticipate that hemorrhage will lead to a linear decrease in the venous waveform signal obtained through both direct intravenous access and the NIVA, regardless of vasoactive pharmacology. Such a result would confirm that the NIVA signal is more sensitive than standard vital signs in detecting blood loss due to hemorrhage.
The second aim i s to determine the effect of cardiac arrhythmias on NIVA signal analyses using a hemodynamic flow loop. Atrial fibrillation is the most common arrhythmia in CHF patients, and leads to an irregularly irregular heart rate which may confound NIVA signal. To determine the effect of atrial fibrillation on the NIVA signal, fresh porcine saphenous vein will be embedded in a methacrylolyl-based hydrogel to mimic the extracellular matrix. A ViVitro Superpump will provide physiologic pulsatility and the resulting NIVA- captured waveforms will be captured with a transducer overlying the gel and analyzed with the NIVA algorithm. We anticipate that atrial fibrillation will present a constraint on waveform detection and analysis. NIVA is the first technology to obtain and analyze venous waveform signals for monitoring respiratory rate, heart rate, and volume status. Its applications to outpatient CHF monitoring could significantly reduce the morbidity and mortality associated with the disease by providing non-invasive information that could be used to optimize medical management.
Congestive heart failure (CHF) results in significant morbidities, namely shortness of breath and leg swelling, and is the leading cause of hospitalization in the United States. This project will advance the development of an accurate, non-invasive, inexpensive, easy-to-use device to measure volume status in CHF patients, allowing for timely medical therapy. The long-term goal is to prevent costly hospital readmissions, improve quality of life, and reduce mortality in patients with CHF.
