In the perioperative environment, precise control of intravascular volume status is important. It has been demonstrated that both volume overload and under resuscitation in the perioperative period can increase morbidity, mortality, length of stay, and cost of perioperative care. Unfortunately, clinical signs and current monitoring strategies are unreliable in providing accurate, real time assessments of volume status. This proposal will develop the use of a unique physiologic signal, Non-Invasive Venous waveform Analysis (NIVA), for monitoring intravascular volume status of both hemorrhage and volume overload. Proof of concept data in humans and experimental animal models, demonstrate that NIVA provides a reliable indication of intravascular volume status, supporting the premise of this proposal. This proposal will use an experimental porcine model of controlled hemorrhage, resuscitation, and volume overload resuscitation to validate and refine an algorithm for waveform analysis. NIVA will be tested in further porcine studies and bench-top human saphenous veins in an ex vivo flow loop with a simulated extracellular matrix as a controlled model system to determine limitations and mechanisms of NIVA. These studies will be used to mitigate risks associated with the use of NIVA and will lead to a better understanding of venous waveform analysis (for precise management of intravascular volume) and of venous hemodynamics (a largely under studied part of the cardiovascular system).
Non-invasive methods to determine intravascular volume status prior to hemodynamic instability or volume overload, represent a large unmet need. This project seeks to understand and optimize the use of a novel physiologic signal, the venous waveform, to derive information about the effects of hemorrhage/volume over resuscitation on venous waveforms, the harmonic generation in the volume overload setting, and effects of supraventricular arrhythmias. This information will be used to assist in determining the best goal-directed care for perioperative patients which will prevent complications due to under resuscitation and over resuscitation, this will likely decrease hospital costs and reduce morbidity and mortality in perioperative patients.