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首页> 外文期刊>European journal of heart failure: journal of the Working Group on Heart Failure of the European Society of Cardiology >Assessment of a novel device-based diagnostic algorithm to monitor patient status in moderate-to-severe heart failure: rationale and design of the CLEPSYDRA study.
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Assessment of a novel device-based diagnostic algorithm to monitor patient status in moderate-to-severe heart failure: rationale and design of the CLEPSYDRA study.

机译：评估基于新型设备的诊断算法以监测中度至重度心力衰竭患者的状态：CLEPSYDRA研究的原理和设计。

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AIMS: Monitoring systems integrated into electronic implantable devices for heart failure (HF) have significantly expanded the possibility of obtaining diagnostic information and can be used to enhance patient follow-up. The ability to obtain advance warning of worsening HF is currently being explored using a variety of diagnostic parameters. A novel device-based algorithm, physiological diagnostic (PhD), combines data from minute ventilation and accelerometer sensors to provide an indicator of the overall status of HF patients and detect clinically relevant acute HF events. The objective of this study was to evaluate the effectiveness of the PhD algorithm for detecting HF events in patients with HF. METHODS: CLEPSYDRA is a multicentre, prospective, non-randomized, single-arm double-blinded study in 62 centres in Europe, the USA, and Canada. Patients with moderate-to-severe HF, on stable optimal pharmacological therapy, QRS>/=120 ms, and ejection fraction
机译：目标：集成到用于心脏衰竭（HF）的电子可植入设备中的监视系统已大大扩展了获取诊断信息的可能性，并可用于加强对患者的随访。当前正在使用各种诊断参数来探索获得有关HF恶化的预警的能力。一种基于设备的新颖算法，即生理诊断（PhD），它结合了分钟通气和加速计传感器的数据，可为HF患者的整体状况提供指标并检测临床相关的急性HF事件。这项研究的目的是评估PhD算法检测HF患者的HF事件的有效性。方法：CLEPSYDRA是一项在欧洲，美国和加拿大的62个中心进行的多中心，前瞻性，非随机，单臂双盲研究。包括中度至重度HF，经过稳定的最佳药物治疗，QRS> / = 120 ms，射血分数

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