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Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation
BACKGROUND: Some patients with COVID-19 experienced sudden death due to rapid symptom deterioration. Thus, it is important to predict COVID-19 symptom exacerbation at an early stage prior to increasing severity in patients. Patients with COVID-19 could experience a unique “silent hypoxia” at an earl...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448084/ https://www.ncbi.nlm.nih.gov/pubmed/34516390 http://dx.doi.org/10.2196/30819 |
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author | Yamagami, Kan Nomura, Akihiro Kometani, Mitsuhiro Shimojima, Masaya Sakata, Kenji Usui, Soichiro Furukawa, Kenji Takamura, Masayuki Okajima, Masaki Watanabe, Kazuyoshi Yoneda, Takashi |
author_facet | Yamagami, Kan Nomura, Akihiro Kometani, Mitsuhiro Shimojima, Masaya Sakata, Kenji Usui, Soichiro Furukawa, Kenji Takamura, Masayuki Okajima, Masaki Watanabe, Kazuyoshi Yoneda, Takashi |
author_sort | Yamagami, Kan |
collection | PubMed |
description | BACKGROUND: Some patients with COVID-19 experienced sudden death due to rapid symptom deterioration. Thus, it is important to predict COVID-19 symptom exacerbation at an early stage prior to increasing severity in patients. Patients with COVID-19 could experience a unique “silent hypoxia” at an early stage of the infection when they are apparently asymptomatic, but with rather low SpO(2) (oxygen saturation) levels. In order to continuously monitor SpO(2) in daily life, a high-performance wearable device, such as the Apple Watch or Fitbit, has become commercially available to monitor several biometric data including steps, resting heart rate (RHR), physical activity, sleep quality, and estimated oxygen variation (EOV). OBJECTIVE: This study aimed to test whether EOV measured by the wearable device Fitbit can predict COVID-19 symptom exacerbation. METHODS: We recruited patients with COVID-19 from August to November 2020. Patients were asked to wear the Fitbit for 30 days, and biometric data including EOV and RHR were extracted. EOV is a relative physiological measure that reflects users’ SpO(2) levels during sleep. We defined a high EOV signal as a patient’s oxygen level exhibiting a significant dip and recovery within the index period, and a high RHR signal as daily RHR exceeding 5 beats per day compared with the minimum RHR of each patient in the study period. We defined successful prediction as the appearance of those signals within 2 days before the onset of the primary outcome. The primary outcome was the composite of deaths of all causes, use of extracorporeal membrane oxygenation, use of mechanical ventilation, oxygenation, and exacerbation of COVID-19 symptoms, irrespective of readmission. We also assessed each outcome individually as secondary outcomes. We made weekly phone calls to discharged patients to check on their symptoms. RESULTS: We enrolled 23 patients with COVID-19 diagnosed by a positive SARS-CoV-2 polymerase chain reaction test. The patients had a mean age of 50.9 (SD 20) years, and 70% (n=16) were female. Each patient wore the Fitbit for 30 days. COVID-19 symptom exacerbation occurred in 6 (26%) patients. We were successful in predicting exacerbation using EOV signals in 4 out of 5 cases (sensitivity=80%, specificity=90%), whereas the sensitivity and specificity of high RHR signals were 50% and 80%, respectively, both lower than those of high EOV signals. Coincidental obstructive sleep apnea syndrome confirmed by polysomnography was detected in 1 patient via consistently high EOV signals. CONCLUSIONS: This pilot study successfully detected early COVID-19 symptom exacerbation by measuring EOV, which may help to identify the early signs of COVID-19 exacerbation. TRIAL REGISTRATION: University Hospital Medical Information Network Clinical Trials Registry UMIN000041421; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047290 |
format | Online Article Text |
id | pubmed-8448084 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-84480842021-10-06 Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation Yamagami, Kan Nomura, Akihiro Kometani, Mitsuhiro Shimojima, Masaya Sakata, Kenji Usui, Soichiro Furukawa, Kenji Takamura, Masayuki Okajima, Masaki Watanabe, Kazuyoshi Yoneda, Takashi JMIR Form Res Original Paper BACKGROUND: Some patients with COVID-19 experienced sudden death due to rapid symptom deterioration. Thus, it is important to predict COVID-19 symptom exacerbation at an early stage prior to increasing severity in patients. Patients with COVID-19 could experience a unique “silent hypoxia” at an early stage of the infection when they are apparently asymptomatic, but with rather low SpO(2) (oxygen saturation) levels. In order to continuously monitor SpO(2) in daily life, a high-performance wearable device, such as the Apple Watch or Fitbit, has become commercially available to monitor several biometric data including steps, resting heart rate (RHR), physical activity, sleep quality, and estimated oxygen variation (EOV). OBJECTIVE: This study aimed to test whether EOV measured by the wearable device Fitbit can predict COVID-19 symptom exacerbation. METHODS: We recruited patients with COVID-19 from August to November 2020. Patients were asked to wear the Fitbit for 30 days, and biometric data including EOV and RHR were extracted. EOV is a relative physiological measure that reflects users’ SpO(2) levels during sleep. We defined a high EOV signal as a patient’s oxygen level exhibiting a significant dip and recovery within the index period, and a high RHR signal as daily RHR exceeding 5 beats per day compared with the minimum RHR of each patient in the study period. We defined successful prediction as the appearance of those signals within 2 days before the onset of the primary outcome. The primary outcome was the composite of deaths of all causes, use of extracorporeal membrane oxygenation, use of mechanical ventilation, oxygenation, and exacerbation of COVID-19 symptoms, irrespective of readmission. We also assessed each outcome individually as secondary outcomes. We made weekly phone calls to discharged patients to check on their symptoms. RESULTS: We enrolled 23 patients with COVID-19 diagnosed by a positive SARS-CoV-2 polymerase chain reaction test. The patients had a mean age of 50.9 (SD 20) years, and 70% (n=16) were female. Each patient wore the Fitbit for 30 days. COVID-19 symptom exacerbation occurred in 6 (26%) patients. We were successful in predicting exacerbation using EOV signals in 4 out of 5 cases (sensitivity=80%, specificity=90%), whereas the sensitivity and specificity of high RHR signals were 50% and 80%, respectively, both lower than those of high EOV signals. Coincidental obstructive sleep apnea syndrome confirmed by polysomnography was detected in 1 patient via consistently high EOV signals. CONCLUSIONS: This pilot study successfully detected early COVID-19 symptom exacerbation by measuring EOV, which may help to identify the early signs of COVID-19 exacerbation. TRIAL REGISTRATION: University Hospital Medical Information Network Clinical Trials Registry UMIN000041421; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047290 JMIR Publications 2021-09-16 /pmc/articles/PMC8448084/ /pubmed/34516390 http://dx.doi.org/10.2196/30819 Text en ©Kan Yamagami, Akihiro Nomura, Mitsuhiro Kometani, Masaya Shimojima, Kenji Sakata, Soichiro Usui, Kenji Furukawa, Masayuki Takamura, Masaki Okajima, Kazuyoshi Watanabe, Takashi Yoneda. Originally published in JMIR Formative Research (https://formative.jmir.org), 16.09.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Yamagami, Kan Nomura, Akihiro Kometani, Mitsuhiro Shimojima, Masaya Sakata, Kenji Usui, Soichiro Furukawa, Kenji Takamura, Masayuki Okajima, Masaki Watanabe, Kazuyoshi Yoneda, Takashi Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation |
title | Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation |
title_full | Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation |
title_fullStr | Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation |
title_full_unstemmed | Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation |
title_short | Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation |
title_sort | early detection of symptom exacerbation in patients with sars-cov-2 infection using the fitbit charge 3 (dexterity): pilot evaluation |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448084/ https://www.ncbi.nlm.nih.gov/pubmed/34516390 http://dx.doi.org/10.2196/30819 |
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