Heart Rate Dynamics in Response to Upper-Extremity Function Test to Identify Irreversible Frailty After Invasive Therapy in Older Adults with Advanced Heart Disease

心率动态对上肢功能测试的反应，以识别患有晚期心脏病的老年人在侵入性治疗后的不可逆转的虚弱

• 批准号: 10582957
• 负责人: Nima Toosizadeh
• 金额: $ 1.45万
• 依托单位: UNIVERSITY OF ARIZONA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10582957
• 关键词: Adverse event; Age; Aortic Valve Stenosis; Arizona; Assessment tool; Beds; Behavior; Biomedical Engineering; Biometry; Cardiac; Cardiology; Cardiopulmonary; Cardiovascular system; Categories; Cause of Death; Characteristics; Chest; Clinical; Clinical Treatment; Cognitive; Data; Disease; Elbow; Elderly; Electrocardiogram; Engineering; Environment; Exercise; Eye; Fatigue; Geriatrics; Goals; Healthcare; Heart; Heart Diseases; Heart Rate; Homeostasis; Inpatients; Lasso; Lead; Left; Legal patent; Machine Learning; Measures; Methods; Mission; Modeling; Morphologic artifacts; Motion; Motor; Outcome; Participant; Patients; Performance; Physical activity; Physiological; Prediction of Response to Therapy; Procedures; Recovery; Replacement Therapy; Research; Risk; Risk Assessment; Sampling; Side; Speed; Stress; Symptoms; System; Testing; Therapeutic; Training; Treatment Cost; Treatment outcome; United States; Universities; Upper Extremity; Vascular blood supply; Walking; adverse outcome; aggressive therapy; aortic valve replacement; arm; candidate identification; candidate selection; clinical care; common treatment; comorbidity; comparison control; cost; design; flexibility; follow-up; frailty; heart function; heart rate monitor; improved; motion sensor; motor disorder; motor impairment; multidisciplinary; multimodality; novel; outcome prediction; predict clinical outcome; programs; resilience; response; risk stratification; sensor; sex; signal processing; stressor; therapy outcome; tool; wearable sensor technology

PROJECT SUMMARY/ABSTRACT Advanced heart diseases lead to a reduced blood supply from the heart and consequently fatigue and deficits in performing physical activity. In the proposed research, we will assess the lack of physiological reserve in older adults with advanced heart disease, focusing on motor and cardiac function, to develop a novel, objective, quick, and accurate frailty score. We designed this approach to enhance candidate selection of older adults going through invasive therapies for advanced heart diseases. Although our approach is generic, to reduce between- subject variability we focus on transcatheter aortic valve replacement (TAVR) for older adult with aortic stenosis. Therapeutic options continue to grow for TAVR; however, it can be difficult to identify candidates with frailty level that prohibit them from tolerating the stress from aggressive therapy and those with potential reversible frailty. It is thus critically important to introduce meaningful routine objective frailty assessment into clinical care of cardiac patients. Frailty assessment is, however, not common in cardiology because current assessment tools are burdensome for older adults with advanced heart disease and impractical to implement in busy clinical environments. More importantly, no disease-specific tool is available to identify heart disease-related frailty. In continuation of our research program in the field of sensor-based frailty assessment, within our multidisciplinary team of engineers, cardiologists, and geriatricians, we propose the multimodal upper-extremity function (UEF) test for identifying frailty among older adults with advanced heart disease. UEF incorporates a synchronized system of motion sensors and electrocardiography (ECG) to measure motor performance and heart rate (HR) during a rapid 20-second elbow flexion task. Using our previously established UEF motion tracking component, we can precisely measure the level of deficits in motor performance (slowness, weakness, inflexibility, and fatigue), which are not detectable using eyeball assessment. Using the ECG setup, minimizing the motion artifact using this localized task, we accurately track HR response to the physical demand, as well as recovery behavior after the task. HR behavior during the task and recovery (HR dynamics) provide a measure of cardiac reserve associated with frailty in heart disease. We will further quantify dysregulation between HR response and motor demand as a novel measure of resilience. Based on our preliminary data, we expect a weaker and delayed HR response to physical activity as well as an impaired motor function due to frailty. The proposed research will be a four-year study at the University of Arizona Cardiovascular program. In the first arm, we will establish a new HR score and merge it with our previously validated UEF motor score to develop a multimodal frailty score among older adults with advanced heart disease (n=120). In the second arm, in a longitudinally setting we will validate the UEF multimodal frailty score for predicting TAVR complications for advanced heart disease (n=75). Accomplishing these aims, we will promote HR dynamic assessment for risk stratification of older adults with advanced heart disease, with huge potentials for other comorbid conditions.

项目摘要/摘要 晚期心脏病会导致心脏供血减少，从而导致心脏疲劳和心脏功能缺陷. 进行体力活动。在拟议的研究中，我们将评估老年人缺乏生理储备的情况。 成人心脏病晚期，注重运动和心脏功能，开发新颖、客观、快速、 和准确的脆弱分数。我们设计这一方法是为了加强老年人的候选人选择 通过侵入性疗法治疗晚期心脏病。虽然我们的方法是通用的，但要减少- 主题变异性我们关注老年主动脉狭窄患者的经导管主动脉瓣置换术(TAVR)。 TAVR的治疗选择继续增加；然而，很难确定脆弱程度的候选者 这禁止他们忍受来自积极治疗的压力，以及那些具有潜在可逆脆弱的人。它 因此，将有意义的常规客观脆弱性评估引入心脏临床护理是至关重要的 病人。然而，脆弱评估在心脏病学中并不常见，因为目前的评估工具是 对患有晚期心脏病的老年人来说是负担，在繁忙的临床中实施不切实际 环境。更重要的是，目前还没有针对特定疾病的工具来识别与心脏病相关的脆弱性。 为了继续我们在基于传感器的脆弱性评估领域的研究计划，在我们的 由工程师、心脏病专家和老年医生组成的多学科团队，我们提出了多模式上肢 用于识别患有晚期心脏病的老年人的虚弱程度的功能(UEF)试验。UEF合并了一个 运动传感器和心电图仪的同步系统，用于测量运动性能和 快速屈肘20秒时的心率(HR)。使用我们先前建立的UEF动议 跟踪组件，我们可以精确地测量运动性能缺陷的水平(缓慢，虚弱， 不灵活和疲劳)，这些都是用眼球评估无法检测到的。使用心电设置，最小化 运动伪像使用这种局部化的任务，我们准确地跟踪HR对物理需求的响应，以及 任务完成后的恢复行为。任务期间的人力资源行为和恢复(人力资源动态)提供了一种衡量标准 心脏储备与心脏病的虚弱有关。我们将进一步量化人力资源之间的失调 反应和运动需求作为一种新的弹性衡量标准。根据我们的初步数据，我们预计 对体力活动的心率反应较弱和延迟，以及由于虚弱而导致的运动功能受损。 这项拟议的研究将是亚利桑那大学心血管项目的一项为期四年的研究。在第一个 ARM，我们将建立一个新的HR评分，并将其与我们之前验证的UEF运动评分合并，以开发 老年晚期心脏病患者的多模式脆弱评分(n=120)。在第二个手臂中，在一个 在纵向设置下，我们将验证UEF多模式脆弱性评分对TAVR并发症的预测 晚期心脏病75例。为实现这些目标，我们将推动人力资源风险动态评估 对患有晚期心脏病的老年人进行分层，并对其他并存疾病具有巨大的潜力。