Yapejian Andrea Rebecca, Fudim Marat
Department of Medicine, Duke University Hospital, Durham, NC, USA.
Eur Heart J Case Rep. 2021 Feb 20;5(2):ytab067. doi: 10.1093/ehjcr/ytab067. eCollection 2021 Feb.
With the ongoing coronavirus disease 2019 (COVID-19) epidemic, remote monitoring of patients with implanted cardiac devices has become more important than ever, as physical distancing measures have placed limits on in-clinic device monitoring. Remote monitoring alerts, particularly those associated with heart failure trends, have proved useful in guiding care in regard to monitoring fluid status and adjusting heart failure medications.
This report describes use of Boston Scientific's HeartLogic algorithm, which is a multisensor device algorithm in implantable cardioverter-defibrillator devices that is proven to be an early predictor of heart failure decompensation by measuring several variables, including respiratory rate, nighttime heart rate, and heart sounds. We present three cases of patients who were actively surveilled by the various HeartLogic device algorithm sensors and were identified to have increasing respiratory rates high enough to trigger a HeartLogic alert prior to a positive COVID-19 diagnosis.
We propose that the HeartLogic algorithm and its accompanying individual physiologic sensors demonstrate potential for use in identifying non-heart failure-related decompensation, such as COVID-19-positive diagnoses.
随着2019冠状病毒病（COVID-19）疫情的持续，对植入心脏装置患者的远程监测变得比以往任何时候都更加重要，因为物理距离措施限制了在诊所内对装置的监测。远程监测警报，尤其是那些与心力衰竭趋势相关的警报，已被证明有助于指导对液体状态的监测和调整心力衰竭药物治疗。
本报告描述了波士顿科学公司的HeartLogic算法的使用情况，该算法是植入式心脏复律除颤器装置中的一种多传感器装置算法，通过测量包括呼吸频率、夜间心率和心音在内的多个变量，被证明是心力衰竭失代偿的早期预测指标。我们介绍了三例患者，他们通过HeartLogic装置算法的各种传感器进行了积极监测，并在COVID-19确诊之前被确定呼吸频率升高到足以触发HeartLogic警报。
我们认为，HeartLogic算法及其附带的个体生理传感器显示出可用于识别与心力衰竭无关的失代偿情况的潜力，如COVID-19阳性诊断。
