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Zhang C, Sun A, Liao J, Zhang C, Yu K, Ma X, Wang G. COVID-19 surveillance based on consumer wearable devices. Digit Health 2024; 10:20552076241247374. [PMID: 38665889 PMCID: PMC11044784 DOI: 10.1177/20552076241247374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 03/15/2024] [Indexed: 04/28/2024] Open
Abstract
Background Consumer wearable devices such as wristbands and smartwatches have potential application value in communicable disease surveillance. Objective We investigated the ability of wearable devices to monitor COVID-19 patients of varying severity. Methods COVID-19 patients with mobile phones supporting wearable device applications were selected from Dalian Sixth People Hospital. Physiological parameters from the wearable devices and electronic questionnaires were collected from the device wearing until 14 days post-discharge. Clinical information during hospitalization was also recorded. Based on imaging data, the patients were categorized into the milder group without pneumonia and the more severe group with pneumonia. We plotted the curves of the physiological parameters of the two groups to compare the differences and changes. Results Ninety-eight patients were included in the analysis. The mean age was 39.6 ± 10.5 years, including 45 males (45.9%). There were 24 asymptomatic patients, 10 mild patients, 60 moderate patients, and 4 severe patients. Compared with the milder group, the more severe group had higher heart rate-related parameters, while the heart rate variability (HRV) was the opposite. In the more severe group, the heart rate-related parameters showed a downward trend from 0 to 7 days after the fever resolution. Among them, the resting heart rate and sleep heart rate decreased on the 25th day after the onset and were close to the milder group 1 week after discharge. Conclusions Consumer wearable devices have the potential to monitor respiratory infections. Heart rate-related parameters obtained from these devices can be sensitive indicators of COVID-19 severity and correlate with disease evolution. Trial registration ClinicalTrials.gov NCT04459637.
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Affiliation(s)
- Chunbo Zhang
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Aijun Sun
- Dalian Sixth People Hospital, Dalian, Liaoning, China
| | - Jiping Liao
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Chunbo Zhang
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Kunyao Yu
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Xiaoyu Ma
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Guangfa Wang
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
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Chow JSF, D’Souza A, Ford M, Marshall S, San Miguel S, Parameswaran A, Parsons M, Ramirez J, Teramayi R, Maurya N. A descriptive study of the clinical impacts on COVID-19 survivors using telemonitoring (The TeleCOVID Study). FRONTIERS IN MEDICAL TECHNOLOGY 2023; 5:1126258. [PMID: 37020492 PMCID: PMC10067568 DOI: 10.3389/fmedt.2023.1126258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Accepted: 03/02/2023] [Indexed: 04/07/2023] Open
Abstract
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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Affiliation(s)
- Josephine Sau Fan Chow
- Clinical Innovation & Business Unit, South Western Sydney Local Health District, Sydney, NSW, Australia
- SouthWestern Sydney Nursing and Midwifery Research Alliance, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia
- Faculty of Medicine, University of New South Wales, Sydney, NSW,Australia
- Faculty of Medicine, Western Sydney University, Sydney, NSW, Australia
- Correspondence: Josephine Sau Fan Chow
| | - Annamarie D’Souza
- Research Directorate, South Western Sydney Local Health District, Liverpool, NSW, Australia
| | - Megan Ford
- Clinical Trial Support Unit, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Sonia Marshall
- District Nursing and Midwifery Office, South Western Sydney Local Health District, Liverpool, NSW, Australia
| | - Susana San Miguel
- Clinical Innovation & Business Unit, South Western Sydney Local Health District, Sydney, NSW, Australia
| | - Ahilan Parameswaran
- Emergency Department, Bankstown Hospital, South Western Sydney Local Health District, Liverpool, NSW, Australia
| | - Mark Parsons
- Faculty of Medicine, University of New South Wales, Sydney, NSW,Australia
- Neurology Research Unit, South Western Sydney Local Health District, Liverpool, NSW, Australia
| | - Jacqueline Ramirez
- Clinical Innovation & Business Unit, South Western Sydney Local Health District, Sydney, NSW, Australia
- SouthWestern Sydney Nursing and Midwifery Research Alliance, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia
| | - Rumbidzai Teramayi
- Neurology Research Unit, South Western Sydney Local Health District, Liverpool, NSW, Australia
| | - Nutan Maurya
- Clinical Innovation & Business Unit, South Western Sydney Local Health District, Sydney, NSW, Australia
- SouthWestern Sydney Nursing and Midwifery Research Alliance, Ingham Institute for Applied Medical Research, Sydney, NSW, Australia
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