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POWRE: Signal Processing of Spontaneous Arrhythmias Acquired Chronically in an Adriamycin Model of Heart Failure

POWRE: Signal Processing of Spontaneous Arrhythmias Acquired Chronically in an Adriamycin Model of Heart Failure
POWRE:阿霉素心力衰竭模型中慢性自发性心律失常的信号处理
批准号:
9973513
负责人:
Stephanie Schuckers
金额:
$8.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1999
资助国家:
美国
项目状态:
已结题
起止时间:
1999-07-01 至 2002-12-31

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中文摘要
翻译
9973513 schuckers在美国,有一百万到两百万的成年人患有心力衰竭,每年有20万人死亡。这些死亡中有30-50%是突然死亡,并归因于心电异常。心电学是研究心脏电特性的学科,在预测和预防心源性猝死方面起着重要作用。虽然已经进行了大量的研究,试图预测心源性猝死,但没有长期的研究跟踪从正常到病变状态的心电图进展。此外,为了建立心源性猝死的短期电生理预测指标,对自发性事件发生前数周、数天和数小时的心电图(ECG)进行分析的工作很少。如果可以预测猝死事件,可以尝试长期和短期干预措施来预防这一事件。本提案的总体目标是建立和使用阿霉素家兔心力衰竭模型来研究从正常到猝死事件的心电图进展。动物将配备长期植入的心电图系统。脑电图将通过射频遥测连续记录动物的一生。经典的心电图特征和创新的特征将由计算机计算,并在动物的整个生命周期中进行监测,其中将特别注意事件发生前的变化。这项工作的主要目标是开发一种短期预测方案,该方案可以预测即将发生的事件,以便在临床环境中进行预防/干预,如电疗法。
英文摘要
9973513SchuckersOne to two million adults are affected in the United States by heart failure with 200,000 deaths annually. 30-50% of these deaths are sudden and have been attributed to cardiac electrical abnormalities. Electrocardiology, the study of electrical characteristics of the heart, plays a major role in prediction and prevention of sudden cardiac death. Although much research has been performed to attempt to predict sudden cardiac death, no long-term studies have tracked the electrocardiographic progression from normal to diseased state. Furthermore, little work has been done to analyze the electrocardiogram (ECG) in the weeks, days, and hours before a spontaneous event in order to establish a short-term electrophysiologic predictor of sudden cardiac death. If a sudden death episode could be predicted, long- and short-term interventions could be attempted to prevent the event. The overall goal of this proposal is to develop and use an adriamycin rabbit model of heart failure to study the electrocardiographic progression from normal to a sudden death event. Animals will be outfitted with a long-term implanted ECG system. ECGs will be recorded continuously for the lifetime of the animal through radiofrequency-telemetry. Classical ECG features as well as innovative features will be calculated by computer and monitored over the lifetime of the animal where particular attention will be paid to changes preceding an event. The main goal of this work will be the development of a short-term prediction scheme which could predict an impending event such that in the clinical setting preventions/interventions, like electrical therapies may be performed.
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