使用远程监护对COVID-19幸存者临床影响的描述性研究(TeleCOVID研究)。

Josephine Sau Fan Chow, Annamarie D'Souza, Megan Ford, Sonia Marshall, Susana San Miguel, Ahilan Parameswaran, Mark Parsons, Jacqueline Ramirez, Rumbidzai Teramayi, Nutan Maurya
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引用次数: 0

摘要

背景:越来越多的证据表明,COVID-19幸存者在感染后出现各种心血管并发症的风险增加;然而,目前还没有经过验证的模型或明确的指南来远程监测COVID-19幸存者的心脏健康。目的:本研究旨在测试一种用于检测COVID-19幸存者临床症状及其影响的虚拟家庭医疗保健监测模型。验证系统的可用性和可行性。方法:这项开放标签、前瞻性、描述性研究在悉尼西南部进行。该研究包括2021年6月至2021年11月期间因诊断为COVID-19而入院的患者。在同意后,为符合条件的参与者提供脉搏血氧仪来测量氧饱和度,并提供S-Patch EX来监测他们的心电图(ECG),持续3个月。数据通过蓝牙技术实时传输到手机上,结果通过云平台发送给研究小组。研究小组及时审查了所有数据,以了解COVID-19后相关症状,如血氧饱和度降低和心律失常。结果测量:本研究旨在考虑在真实临床环境中实施的可行性,使研究团队能够开发和利用虚拟的家庭医疗保健监测模型来检测COVID-19后临床症状和对COVID-19幸存者的影响。结果:研究期间,有23例患者同意参与。其中19例患者开始监测。16例患者81例(73.6%)有效试验纳入分析,其中7例患者经人工智能检测为心律失常,但无临床症状。心律失常患者室上异位发生率较高,且多数患者在检测前至少做过2次检查。值得注意的是,有心律失常的患者比没有心律失常的患者进行了更多的检查[t检验,t (13) = 2.29, p]。结论:初步观察发现,在完成3个月随访的前16名参与者中,有7人在长时间心脏监测中发现心律失常。这使得他们的治疗医生能够及早了解情况,进行进一步调查和早期干预。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A descriptive study of the clinical impacts on COVID-19 survivors using telemonitoring (The TeleCOVID Study).

Background: There is increasing evidence that COVID-19 survivors are at increased risk of experiencing a wide range of cardiovascular complications post infection; however, there are no validated models or clear guidelines for remotely monitoring the cardiac health of COVID-19 survivors.

Objective: This study aims to test a virtual, in-home healthcare monitoring model of care for detection of clinical symptoms and impacts on COVID-19 survivors. It also aims to demonstrate system usability and feasibility.

Methods: This open label, prospective, descriptive study was conducted in South Western Sydney. Included in the study were patients admitted to the hospital with the diagnosis of COVID-19 between June 2021 and November 2021. Eligible participants after consent were provided with a pulse oximeter to measure oxygen saturation and a S-Patch EX to monitor their electrocardiogram (ECG) for a duration of 3 months. Data was transmitted in real-time to a mobile phone via Bluetooth technology and results were sent to the study team via a cloud-based platform. All the data was reviewed in a timely manner by the investigator team, for post COVID-19 related symptoms, such as reduction in oxygen saturation and arrhythmia.

Outcome measure: This study was designed for feasibility in real clinical setting implementation, enabling the study team to develop and utilise a virtual, in-home healthcare monitoring model of care to detect post COVID-19 clinical symptoms and impacts on COVID-19 survivors.

Results: During the study period, 23 patients provided consent for participation. Out of which 19 patients commenced monitoring. Sixteen patients with 81 (73.6%) valid tests were included in the analysis and amongst them seven patients were detected by artificial intelligence to have cardiac arrhythmias but not clinically symptomatic. The patients with arrhythmias had a higher occurrence of supraventricular ectopy, and most of them took at least 2 tests before detection. Notably, patients with arrhythmia had significantly more tests than those without [t-test, t (13) = 2.29, p < 0.05].

Conclusions: Preliminary observations have identified cardiac arrhythmias on prolonged cardiac monitoring in 7 out of the first 16 participants who completed their 3 months follow-up. This has allowed early escalation to their treating doctors for further investigations and early interventions.

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