Duke Clinical Research Institute (M.F., A.D.D.), Duke University School of Medicine, Durham, NC.
Department of Medicine (M.F., A.D.D.), Duke University School of Medicine, Durham, NC.
Circ Heart Fail. 2023 May;16(5):e010012. doi: 10.1161/CIRCHEARTFAILURE.122.010012. Epub 2023 May 16.
There is a need for simple, noninvasive solutions to remotely monitor and predict worsening heart failure (HF) events. SCALE-HF 1 (Surveillance and Alert-Based Multiparameter Monitoring to Reduce Worsening Heart Failure Events) is a prospective, multicenter study that will develop and assess the accuracy of the heart function index-a composite algorithm of noninvasive hemodynamic biomarkers from a cardiac scale-in predicting worsening HF events.
Approximately 300 patients with chronic HF and recent decompensation will be enrolled in this observational study for model development. Patients will be encouraged to take daily cardiac scale measurements.
Approximately 50 HF events, defined as an urgent, unscheduled clinic, emergency department, or hospitalization for worsening HF will be used for model development. The composite index will be developed from hemodynamic biomarkers derived from ECG, ballistocardiogram, and impedance plethysmogram signals measured from the cardiac scale. Biomarkers of interest include weight, peripheral impedance, pulse rate and variability, and estimates of stroke volume, cardiac output, and blood pressure captured through the cardiac scale. The sensitivity, unexplained alert rate, and alerting time of the index in predicting worsening HF events will be evaluated and compared with the performance of simple weight-based rule-of-thumb algorithms (eg, weight increase of 3 lbs in 1 day or 5 lbs in 7 days) that are often used in practice.
SCALE-HF 1 is the first study to develop and evaluate the performance of a composite index derived from noninvasive hemodynamic biomarkers measured from a cardiac scale in predicting worsening HF events. Subsequent studies will validate the heart function index and assess its ability to improve patient outcomes.
URL: https://www.
gov; Unique identifier: NCT04882449.
需要简单、无创的解决方案来远程监测和预测心力衰竭（HF）恶化事件。SCALE-HF 1（基于监测和警报的多参数监测以减少心力衰竭恶化事件）是一项前瞻性、多中心研究，旨在开发和评估心脏功能指数的准确性——一种由心脏秤的无创血流动力学生物标志物组成的复合算法，用于预测 HF 恶化事件。
大约 300 名患有慢性 HF 和近期失代偿的患者将被纳入这项观察性研究，以进行模型开发。患者将被鼓励每天进行心脏秤测量。
大约 50 例 HF 事件将用于模型开发，定义为 HF 恶化的紧急、非计划的门诊、急诊或住院。复合指数将由从心电图、振动心动描记图和阻抗体积描记图信号中得出的血流动力学生物标志物开发。感兴趣的生物标志物包括体重、外周阻抗、脉搏率和变异性，以及通过心脏秤捕获的估计心输出量、心输出量和血压。该指数预测 HF 恶化事件的灵敏度、未解释的警报率和警报时间将与实践中常用的简单体重基准算法（例如，1 天内体重增加 3 磅或 7 天内体重增加 5 磅）的性能进行评估和比较。
SCALE-HF 1 是第一项开发和评估从心脏秤测量的无创血流动力学生物标志物得出的复合指数在预测 HF 恶化事件中的性能的研究。随后的研究将验证心脏功能指数，并评估其改善患者预后的能力。
网址：https://www.clinicaltrials.gov；独特标识符：NCT04882449。
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