Department of Cardiovascular Surgery, Osaka University Graduate School of Medicine.
Department of Chronic Heart Failure Management Global Center for Medical Engineering and Informatics, Osaka University.
Circ J. 2022 Jun 24;86(7):1081-1091. doi: 10.1253/circj.CJ-21-0590. Epub 2021 Dec 11.
Early detection of worsening heart failure (HF) with a telemonitoring system crucially depends on monitoring parameters. The present study aimed to examine whether a serial follow up of all-night respiratory stability time (RST) built into a telemonitoring system could faithfully reflect ongoing deterioration in HF patients at home and detect early signs of worsening HF in a multicenter, prospective study.
Seventeen subjects with New York Heart Association class II or III were followed up for a mean of 9 months using a newly developed telemonitoring system equipped with non-attached sensor technologies and automatic RST analysis. Signals from the home sensor were transferred to a cloud server, where all-night RSTs were calculated every morning and traced by the monitoring center. During the follow up, 9 episodes of admission due to worsening HF and 1 episode of sudden death were preceded by progressive declines of RST. The receiver operating characteristic curve demonstrated that the progressive or sustained reduction of RST below 20 s during 28 days before hospital admission achieved the highest sensitivity of 90.0% and specificity of 81.7% to subsequent hospitalization, with an area under the curve of 0.85.
RST could serve as a sensitive and specific indicator of worsening HF and allow the detection of an early sign of clinical deterioration in the telemedical management of HF.
使用远程监测系统早期检测心力衰竭（HF）恶化情况至关重要，这取决于监测参数。本研究旨在探讨通过远程监测系统连续监测整夜呼吸稳定性时间（RST）是否能够真实反映在家中 HF 患者的病情恶化情况，并在多中心前瞻性研究中发现 HF 恶化的早期迹象。
17 名纽约心脏协会（NYHA）心功能 II 或 III 级的患者使用新开发的远程监测系统进行了平均 9 个月的随访，该系统配备了非附着式传感器技术和自动 RST 分析。家庭传感器的信号被传输到云服务器，那里每天早上都会计算整夜的 RST 并由监测中心跟踪。在随访期间，9 例因 HF 恶化而住院的病例和 1 例猝死病例均在 RST 进行性下降之前发生。受试者工作特征曲线显示，在住院前 28 天内 RST 持续或逐渐降至 20 秒以下，对随后的住院治疗具有最高的敏感性（90.0%）和特异性（81.7%），曲线下面积为 0.85。
RST 可作为 HF 恶化的敏感和特异性指标，允许在 HF 的远程医疗管理中检测到临床恶化的早期迹象。
