Artificial intelligence-enhanced electrocardiography for early assessment of coronavirus disease 2019 severity

Despite challenges in severity scoring systems, artificial intelligence-enhanced electrocardiography (AI-ECG) could assist in early coronavirus disease 2019 (COVID-19) severity prediction. Between March 2020 and June 2022, we enrolled 1453 COVID-19 patients (mean age: 59.7 ± 20.1 years; 54.2% male)...

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Published inScientific reports Vol. 13; no. 1; pp. 15187 - 10
Main Authors Baek, Yong-Soo, Jo, Yoonsu, Lee, Sang-Chul, Choi, Wonik, Kim, Dae-Hyeok
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 13.09.2023
Nature Publishing Group
Nature Portfolio
Subjects
692/308
692/4019
692/699
Algorithms
Artificial intelligence
Coronaviruses
COVID-19
EKG
Electrocardiography
Emergency medical care
Humanities and Social Sciences
multidisciplinary
Science
Science (multidisciplinary)
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Summary:Despite challenges in severity scoring systems, artificial intelligence-enhanced electrocardiography (AI-ECG) could assist in early coronavirus disease 2019 (COVID-19) severity prediction. Between March 2020 and June 2022, we enrolled 1453 COVID-19 patients (mean age: 59.7 ± 20.1 years; 54.2% male) who underwent ECGs at our emergency department before severity classification. The AI-ECG algorithm was evaluated for severity assessment during admission, compared to the Early Warning Scores (EWSs) using the area under the curve (AUC) of the receiver operating characteristic curve, precision, recall, and F1 score. During the internal and external validation, the AI algorithm demonstrated reasonable outcomes in predicting COVID-19 severity with AUCs of 0.735 (95% CI: 0.662–0.807) and 0.734 (95% CI: 0.688–0.781). Combined with EWSs, it showed reliable performance with an AUC of 0.833 (95% CI: 0.830–0.835), precision of 0.764 (95% CI: 0.757–0.771), recall of 0.747 (95% CI: 0.741–0.753), and F1 score of 0.747 (95% CI: 0.741–0.753). In Cox proportional hazards models, the AI-ECG revealed a significantly higher hazard ratio (HR, 2.019; 95% CI: 1.156–3.525, p  = 0.014) for mortality, even after adjusting for relevant parameters. Therefore, application of AI-ECG has the potential to assist in early COVID-19 severity prediction, leading to improved patient management.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-42252-5