Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta‐analysis
Abstract Background The prevalence of atrial fibrillation (AFib) continues to increase globally, posing a significant risk for serious cardiovascular complications, such as ischemic stroke and thromboembolism. Smartwatch single‐lead electrocardiogram (ECG) can be a practical and accurate early detec...
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | Journal of Arrhythmia |
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| Online Access: | https://doi.org/10.1002/joa3.70087 |
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| author | Dr. Muhammad Iqhrammullah Prof. Asnawi Abdullah Dr. Hermansyah Fahmi Ichwansyah Prof. Dr. Ir. Hafnidar A. Rani Meulu Alina Artha M. T. Simanjuntak Derren D. C. H. Rampengan dr. Seba Talat Al‐Gunaid dr. Naufal Gusti dr. Arditya Damarkusuma Edza Aria Wikurendra |
| author_facet | Dr. Muhammad Iqhrammullah Prof. Asnawi Abdullah Dr. Hermansyah Fahmi Ichwansyah Prof. Dr. Ir. Hafnidar A. Rani Meulu Alina Artha M. T. Simanjuntak Derren D. C. H. Rampengan dr. Seba Talat Al‐Gunaid dr. Naufal Gusti dr. Arditya Damarkusuma Edza Aria Wikurendra |
| author_sort | Dr. Muhammad Iqhrammullah |
| collection | DOAJ |
| description | Abstract Background The prevalence of atrial fibrillation (AFib) continues to increase globally, posing a significant risk for serious cardiovascular complications, such as ischemic stroke and thromboembolism. Smartwatch single‐lead electrocardiogram (ECG) can be a practical and accurate early detection tool for AFib. Objective The aim of this study was to fill the research gap in evaluating the accuracy and interpretability of smartwatch ECG for early AFib detection. Methods Data derived from indexed literature in the Scopus, Scilit, PubMed, Google Scholar, Web of Science, IEEE, and Cochrane Library databases (as of June 1, 2024) were systematically screened and extracted. The quantitative synthesis was performed using a two‐level mixed‐effects logistic regression model, as well as a proportional analysis with Freeman‐Tukey double transformation on a restricted maximum‐likelihood model. Results The sensitivity and specificity of smartwatch ECG in algorithmic readings were 86% and 94%, respectively. In manual readings, the sensitivity and specificity reached 96% and 95%, respectively. In a brand‐specific subgroup analysis, the algorithmic reading reached a summary area under the curve (sAUC) of 96%, while another brand achieved the highest sAUC of 98% in manual reading. The level of manual interpretability was relatively high with Cohen's Kappa of 0.83, but 3% of ECG results were difficult to read manually. Conclusion This study shows that smartwatch ECG is able to detect AFib with high accuracy, especially through manual reading by trained medical personnel. PROSPERO Registration CRD42024548537 (May 29, 2024). |
| format | Article |
| id | doaj-art-2d6719d6e54f4a1698de60af7885cf89 |
| institution | Kabale University |
| issn | 1880-4276 1883-2148 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
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| series | Journal of Arrhythmia |
| spelling | doaj-art-2d6719d6e54f4a1698de60af7885cf892025-08-20T03:29:52ZengWileyJournal of Arrhythmia1880-42761883-21482025-06-01413n/an/a10.1002/joa3.70087Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta‐analysisDr. Muhammad Iqhrammullah0Prof. Asnawi Abdullah1Dr. Hermansyah2Fahmi Ichwansyah3Prof. Dr. Ir. Hafnidar A. Rani4Meulu Alina5Artha M. T. Simanjuntak6Derren D. C. H. Rampengan7dr. Seba Talat Al‐Gunaid8dr. Naufal Gusti9dr. Arditya Damarkusuma10Edza Aria Wikurendra11Postgraduate Program of Public Health Universitas Muhammadiyah Aceh Banda Aceh IndonesiaPostgraduate Program of Public Health Universitas Muhammadiyah Aceh Banda Aceh IndonesiaPostgraduate Program of Public Health Universitas Muhammadiyah Aceh Banda Aceh IndonesiaPostgraduate Program of Public Health Universitas Muhammadiyah Aceh Banda Aceh IndonesiaDepartment of Civil Engineering Universitas Muhammadiyah Aceh Banda Aceh IndonesiaFaculty of Medicine Universitas Syiah Kuala Banda Aceh IndonesiaFaculty of Medicine Universitas Gadjah Mada Yogyakarta IndonesiaFaculty of Medicine Universitas Sam Ratulangi Manado IndonesiaFaculty of Medicine Universitas Syiah Kuala Banda Aceh IndonesiaPostgraduate Program of Public Health Universitas Muhammadiyah Aceh Banda Aceh IndonesiaDepartment of Cardiology and Vascular Medicine, Faculty of Medicine, Public Health, and Nursing Universitas Gadjah Mada Yogyakarta IndonesiaDepartment of Public Health, Faculty of Health Universitas Nahdlatul Ulama Surabaya Surabaya IndonesiaAbstract Background The prevalence of atrial fibrillation (AFib) continues to increase globally, posing a significant risk for serious cardiovascular complications, such as ischemic stroke and thromboembolism. Smartwatch single‐lead electrocardiogram (ECG) can be a practical and accurate early detection tool for AFib. Objective The aim of this study was to fill the research gap in evaluating the accuracy and interpretability of smartwatch ECG for early AFib detection. Methods Data derived from indexed literature in the Scopus, Scilit, PubMed, Google Scholar, Web of Science, IEEE, and Cochrane Library databases (as of June 1, 2024) were systematically screened and extracted. The quantitative synthesis was performed using a two‐level mixed‐effects logistic regression model, as well as a proportional analysis with Freeman‐Tukey double transformation on a restricted maximum‐likelihood model. Results The sensitivity and specificity of smartwatch ECG in algorithmic readings were 86% and 94%, respectively. In manual readings, the sensitivity and specificity reached 96% and 95%, respectively. In a brand‐specific subgroup analysis, the algorithmic reading reached a summary area under the curve (sAUC) of 96%, while another brand achieved the highest sAUC of 98% in manual reading. The level of manual interpretability was relatively high with Cohen's Kappa of 0.83, but 3% of ECG results were difficult to read manually. Conclusion This study shows that smartwatch ECG is able to detect AFib with high accuracy, especially through manual reading by trained medical personnel. PROSPERO Registration CRD42024548537 (May 29, 2024).https://doi.org/10.1002/joa3.70087arrhythmiaatrial fibrillationECGelectrocardiogramsmartwatch |
| spellingShingle | Dr. Muhammad Iqhrammullah Prof. Asnawi Abdullah Dr. Hermansyah Fahmi Ichwansyah Prof. Dr. Ir. Hafnidar A. Rani Meulu Alina Artha M. T. Simanjuntak Derren D. C. H. Rampengan dr. Seba Talat Al‐Gunaid dr. Naufal Gusti dr. Arditya Damarkusuma Edza Aria Wikurendra Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta‐analysis Journal of Arrhythmia arrhythmia atrial fibrillation ECG electrocardiogram smartwatch |
| title | Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta‐analysis |
| title_full | Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta‐analysis |
| title_fullStr | Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta‐analysis |
| title_full_unstemmed | Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta‐analysis |
| title_short | Accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation: A systematic review and meta‐analysis |
| title_sort | accuracy and interpretability of smartwatch electrocardiogram for early detection of atrial fibrillation a systematic review and meta analysis |
| topic | arrhythmia atrial fibrillation ECG electrocardiogram smartwatch |
| url | https://doi.org/10.1002/joa3.70087 |
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