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Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study

BACKGROUND: QTc interval monitoring, for the prevention of drug-induced arrhythmias is necessary, especially in the context of coronavirus disease 2019 (COVID-19). For the provision of widespread use, surrogates for 12‑lead ECG QTc assessment may be useful. This prospective observational study compa...

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Autores principales: Maille, Baptiste, Wilkin, Marie, Million, Matthieu, Rességuier, Noémie, Franceschi, Frédéric, Koutbi-Franceschi, Linda, Hourdain, Jérôme, Martinez, Elisa, Zabern, Maxime, Gardella, Christophe, Tissot-Dupont, Hervé, Singh, Jagmeet P., Deharo, Jean-Claude, Fiorina, Laurent
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7845555/
https://www.ncbi.nlm.nih.gov/pubmed/33524462
http://dx.doi.org/10.1016/j.ijcard.2021.01.002
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author Maille, Baptiste
Wilkin, Marie
Million, Matthieu
Rességuier, Noémie
Franceschi, Frédéric
Koutbi-Franceschi, Linda
Hourdain, Jérôme
Martinez, Elisa
Zabern, Maxime
Gardella, Christophe
Tissot-Dupont, Hervé
Singh, Jagmeet P.
Deharo, Jean-Claude
Fiorina, Laurent
author_facet Maille, Baptiste
Wilkin, Marie
Million, Matthieu
Rességuier, Noémie
Franceschi, Frédéric
Koutbi-Franceschi, Linda
Hourdain, Jérôme
Martinez, Elisa
Zabern, Maxime
Gardella, Christophe
Tissot-Dupont, Hervé
Singh, Jagmeet P.
Deharo, Jean-Claude
Fiorina, Laurent
author_sort Maille, Baptiste
collection PubMed
description BACKGROUND: QTc interval monitoring, for the prevention of drug-induced arrhythmias is necessary, especially in the context of coronavirus disease 2019 (COVID-19). For the provision of widespread use, surrogates for 12‑lead ECG QTc assessment may be useful. This prospective observational study compared QTc duration assessed by artificial intelligence (AI-QTc) (Cardiologs®, Paris, France) on smartwatch single‑lead electrocardiograms (SW-ECGs) with those measured on 12‑lead ECGs, in patients with early stage COVID-19 treated with a hydroxychloroquine−azithromycin regimen. METHODS: Consecutive patients with COVID-19 who needed hydroxychloroquine−azithromycin therapy, received a smartwatch (Withings Move ECG®, Withings, France). At baseline, day-6 and day-10, a 12‑lead ECG was recorded, and a SW-ECG was transmitted thereafter. Throughout the drug regimen, a SW-ECG was transmitted every morning at rest. Agreement between manual QTc measurement on a 12‑lead ECG and AI-QTc on the corresponding SW-ECG was assessed by the Bland-Altman method. RESULTS: 85 patients (30 men, mean age 38.3 ± 12.2 years) were included in the study. Fair agreement between manual and AI-QTc values was observed, particularly at day-10, where the delay between the 12‑lead ECG and the SW-ECG was the shortest (−2.6 ± 64.7 min): 407 ± 26 ms on the 12‑lead ECG vs 407 ± 22 ms on SW-ECG, bias −1 ms, limits of agreement −46 ms to +45 ms; the difference between the two measures was <50 ms in 98.2% of patients. CONCLUSION: In real-world epidemic conditions, AI-QTc duration measured by SW-ECG is in fair agreement with manual measurements on 12‑lead ECGs. Following further validation, AI-assisted SW-ECGs may be suitable for QTc interval monitoring. REGISTRATION:ClinicalTrial.govNCT04371744.
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spelling pubmed-78455552021-02-01 Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study Maille, Baptiste Wilkin, Marie Million, Matthieu Rességuier, Noémie Franceschi, Frédéric Koutbi-Franceschi, Linda Hourdain, Jérôme Martinez, Elisa Zabern, Maxime Gardella, Christophe Tissot-Dupont, Hervé Singh, Jagmeet P. Deharo, Jean-Claude Fiorina, Laurent Int J Cardiol Article BACKGROUND: QTc interval monitoring, for the prevention of drug-induced arrhythmias is necessary, especially in the context of coronavirus disease 2019 (COVID-19). For the provision of widespread use, surrogates for 12‑lead ECG QTc assessment may be useful. This prospective observational study compared QTc duration assessed by artificial intelligence (AI-QTc) (Cardiologs®, Paris, France) on smartwatch single‑lead electrocardiograms (SW-ECGs) with those measured on 12‑lead ECGs, in patients with early stage COVID-19 treated with a hydroxychloroquine−azithromycin regimen. METHODS: Consecutive patients with COVID-19 who needed hydroxychloroquine−azithromycin therapy, received a smartwatch (Withings Move ECG®, Withings, France). At baseline, day-6 and day-10, a 12‑lead ECG was recorded, and a SW-ECG was transmitted thereafter. Throughout the drug regimen, a SW-ECG was transmitted every morning at rest. Agreement between manual QTc measurement on a 12‑lead ECG and AI-QTc on the corresponding SW-ECG was assessed by the Bland-Altman method. RESULTS: 85 patients (30 men, mean age 38.3 ± 12.2 years) were included in the study. Fair agreement between manual and AI-QTc values was observed, particularly at day-10, where the delay between the 12‑lead ECG and the SW-ECG was the shortest (−2.6 ± 64.7 min): 407 ± 26 ms on the 12‑lead ECG vs 407 ± 22 ms on SW-ECG, bias −1 ms, limits of agreement −46 ms to +45 ms; the difference between the two measures was <50 ms in 98.2% of patients. CONCLUSION: In real-world epidemic conditions, AI-QTc duration measured by SW-ECG is in fair agreement with manual measurements on 12‑lead ECGs. Following further validation, AI-assisted SW-ECGs may be suitable for QTc interval monitoring. REGISTRATION:ClinicalTrial.govNCT04371744. Elsevier B.V. 2021-05-15 2021-01-29 /pmc/articles/PMC7845555/ /pubmed/33524462 http://dx.doi.org/10.1016/j.ijcard.2021.01.002 Text en © 2021 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Maille, Baptiste
Wilkin, Marie
Million, Matthieu
Rességuier, Noémie
Franceschi, Frédéric
Koutbi-Franceschi, Linda
Hourdain, Jérôme
Martinez, Elisa
Zabern, Maxime
Gardella, Christophe
Tissot-Dupont, Hervé
Singh, Jagmeet P.
Deharo, Jean-Claude
Fiorina, Laurent
Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study
title Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study
title_full Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study
title_fullStr Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study
title_full_unstemmed Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study
title_short Smartwatch Electrocardiogram and Artificial Intelligence for Assessing Cardiac-Rhythm Safety of Drug Therapy in the COVID-19 Pandemic. The QT-logs study
title_sort smartwatch electrocardiogram and artificial intelligence for assessing cardiac-rhythm safety of drug therapy in the covid-19 pandemic. the qt-logs study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7845555/
https://www.ncbi.nlm.nih.gov/pubmed/33524462
http://dx.doi.org/10.1016/j.ijcard.2021.01.002
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