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http://hdl.handle.net/1942/47923| Title: | Remote Monitoring of COVID-19 Patients Following Discharge from a Tertiary Care Center | Authors: | KUMARASAMY, Ganesh DE CANNIERE, Helene VRANKEN, Julie RUTTENS, David Karsmakers, Peter VANDERVOORT, Pieter |
Issue Date: | 2022 | Source: | Proceedingsbook of CinC 2022, | Abstract: | The COVID-19 pandemic has affected people, healthcare systems and caregivers on a global scale causing bottlenecks in hospital resources and overload of healthcare systems. The presence of disease sequelae in patients hospitalized due to COVID-19 warrants additional care and monitoring of these patients. Remote monitoring techniques have been implemented in several domains of healthcare such as cardiology, cardiac rehabilitation and nephrology. Monitoring of vital signs using these technologies has allowed the tracking of patients with more granularity, resulting in better clinical outcomes such as reduction in hospitalizations. Therefore, we hypothesize that remote monitoring is beneficial in managing COVID-19 patients post-hospitalization, enabling home-based patient follow-up. In this study, we investigated the use of remote monitoring on a COVID-19 patient cohort discharged from a tertiary care center. A post-hoc division of patients into two groups (alert-generating patients and non-alert generating patients) was performed. The longitudinal progression of sensor and questionnaire data was studied using linear mixed-effect models. The measured heart rate values were statistically significant in terms of the intercept (p<0.001), indicating a difference between the two patient groups at baseline immediately post-discharge. | Document URI: | http://hdl.handle.net/1942/47923 | DOI: | 10.22489/CinC.2022.231 | Rights: | CinC has been an open-access publication since 2006, in which copyright in each article is held by its authors, who grant permission to copy and redistribute their work with attribution, under the terms of the Creative Commons Attribution License. Earlier volumes appear here courtesy of the IEEE. | Category: | C1 | Type: | Proceedings Paper |
| Appears in Collections: | Research publications |
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| CinC2022-231.pdf | Published version | 289.88 kB | Adobe PDF | View/Open |
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