Non-Invasive Venous waveform Analysis (NIVA) for volume assessment

项目摘要 充血性心力衰竭（CHF）是全球住院的最常见原因， 估计每年仅在美国就有400亿美元。患者最常因肺充血而住院 以及由于容量超负荷引起的呼吸急促，但估计这些住院治疗中有50-80%可能是由于 在出现明显症状之前通过优化医疗来预防。仍然有一个重要的 在门诊CHF环境中对可负担得起的、非侵入性的、实时容量状态监测的未满足需求。 本研究的重点是开发一种无创静脉波形分析（尼瓦）设备， 血流动力学容量评估。尼瓦使用静脉波形分析，而不是常用的 压力分析，以检测由于体积变化而引起的静脉顺应性的变化。这个假设 建议尼瓦将提供一种可靠的、非侵入性的、定量的血管内容量状态测量方法 在CHF门诊患者中。 本研究的第一个目的是描述血流动力学和药理学扰动对 使用猪模型的尼瓦信号。该信息将为优化尼瓦算法提供数据， 减少潜在的混杂变量，如血管活性药物的使用。我们预计出血会 导致通过直接静脉内通路获得的静脉波形信号的线性减小， 尼瓦，不考虑血管活性药理学。这样的结果将证实尼瓦信号更强。 在检测出血所致失血方面，比标准生命体征更敏感。 第二个目的是确定心律失常对尼瓦信号分析的影响， 血流动力学循环房颤是CHF患者最常见的心律失常， 心率不规则，可能混淆尼瓦信号。确定房颤对 将尼瓦信号、新鲜猪隐静脉包埋在甲基丙烯酰基基水凝胶中以模拟 细胞外基质ViVitro Superpump将提供生理脉动性，并产生尼瓦- 用覆盖凝胶的换能器捕获捕获的波形，并用尼瓦算法分析。 我们预期心房颤动将对波形检测和分析提出限制。 尼瓦是第一个获得和分析静脉波形信号以监测呼吸率的技术， 心率和容量状态。其应用于门诊CHF监测可以显着减少 通过提供非侵入性信息， 优化医疗管理。

PROJECT SUMMARY 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 is 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.