Deep learning-based model detects atrial septal defects from electrocardiography: a cross-sectional multicenter hospital-based study

eClinicalMedicine - Tập 63 - Trang 102141 - 2023
Kotaro Miura1,2, Ryuichiro Yagi3,4, Hiroshi Miyama1, Mai Kimura1, Hideaki Kanazawa1, Masahiro Hashimoto5, Sayuki Kobayashi6, Shiro Nakahara6, Tetsuya Ishikawa6, Isao Taguchi6, Motoaki Sano1, Kazuki Sato2, Keiichi Fukuda1, Rahul C. Deo3,4, Calum A. MacRae3,4, Yuji Itabashi6, Yoshinori Katsumata1,2, Shinichi Goto1,3,4,7
1Department of Cardiology, Keio University School of Medicine, Tokyo, Japan
2Institute for Integrated Sports Medicine, Keio University School of Medicine, Tokyo, Japan
3Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, USA
4Harvard Medical School, Boston, MA, USA
5Department of Radiology, Keio University School of Medicine, Tokyo, Japan
6Department of Cardiology, Dokkyo Medical University Saitama Medical Center, Saitama, Japan
7Division of General Internal Medicine & Family Medicine, Department of General and Acute Medicine, Tokai University School of Medicine, Isehara, Japan

Tài liệu tham khảo

Webb, 2006, Atrial septal defect in the adult recent progress and overview, Circulation, 114, 1645, 10.1161/CIRCULATIONAHA.105.592055 Geva, 2014, Atrial septal defects, Lancet, 383, 1921, 10.1016/S0140-6736(13)62145-5 Udholm, 2019, Lifelong burden of small unrepaired atrial septal defect: results from the Danish National Patient Registry, Int J Cardiol, 283, 101, 10.1016/j.ijcard.2019.02.024 Nyboe, 2018, Long-term mortality in patients with atrial septal defect: a nationwide cohort-study, Eur Heart J, 39, 993, 10.1093/eurheartj/ehx687 Brida, 2019, Atrial septal defect closure in adulthood is associated with normal survival in the mid to longer term, Heart, 105, 1014, 10.1136/heartjnl-2018-314380 Heller, 1996, “Crochetage” (Notch) on R wave in inferior limb leads: a new independent electrocardiographic sign of atrial septal defect, J Am Coll Cardiol, 27, 877, 10.1016/0735-1097(95)00554-4 Izumida Goto, 2022, The future role of high-performance computing in cardiovascular medicine and science -impact of multi-dimensional data analysis, J Atherosclerosis Thromb, 29, 559, 10.5551/jat.RV17062 Goto, 2019, Application of neural networks to 12-lead electrocardiography ― current status and future directions ―, Circ Rep, 1, 481, 10.1253/circrep.CR-19-0096 Raghunath, 2020, Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network, Nat Med, 26, 886, 10.1038/s41591-020-0870-z Attia, 2019, An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction, Lancet, 394, 861, 10.1016/S0140-6736(19)31721-0 Goto, 2021, Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms, Nat Commun, 12, 2726, 10.1038/s41467-021-22877-8 Goto, 2019, Artificial intelligence to predict needs for urgent revascularization from 12-leads electrocardiography in emergency patients, PLoS One, 14, 10.1371/journal.pone.0210103 Miura, 2020, Feasibility of the deep learning method for estimating the ventilatory threshold with electrocardiography data, NPJ Digit Med, 3, 141, 10.1038/s41746-020-00348-6 Selvaraju, 2016, Grad-CAM: visual explanations from deep networks via gradient-based localization, Int J Computer Vis, 128, 336, 10.1007/s11263-019-01228-7 Akagi, 2015, Current concept of transcatheter closure of atrial septal defect in adults, J Cardiol, 65, 17 Grignani, 2015, Longitudinal evaluation of P-wave dispersion and P-wave maximum in children after transcatheter device closure of secundum atrial septal defect, Pediatr Cardiol, 36, 1050, 10.1007/s00246-015-1119-3 Thilén, 2009, Atrial myocardial pathoelectrophysiology in adults with a secundum atrial septal defect is unaffected by closure of the defect. A study using high resolution signal-averaged orthogonal P-wave technique, Int J Cardiol, 132, 364, 10.1016/j.ijcard.2007.11.101 Gaba, 2020, Mortality in patients with right bundle-branch block in the absence of cardiovascular disease, J Am Heart Assoc, 9 Maheshwari, 2017, Relation of prolonged P-wave duration to risk of sudden cardiac death in the general population (from the atherosclerosis risk in communities study), Am J Cardiol, 119, 1302, 10.1016/j.amjcard.2017.01.012 Khairy, 2007, Clinical use of electrocardiography in adults with congenital heart disease, Circulation, 116, 2734, 10.1161/CIRCULATIONAHA.107.691568 Deo, 2015, Machine learning in medicine, Circulation, 132, 1920, 10.1161/CIRCULATIONAHA.115.001593 Somani, 2021, Deep learning and the electrocardiogram: review of the current state-of-the-art, Europace, 23, 1179, 10.1093/europace/euaa377 Kwon, 2020, Deep learning–based algorithm for detecting aortic stenosis using electrocardiography, J Am Heart Assoc, 9 Ko, 2020, Detection of hypertrophic cardiomyopathy using a convolutional neural network-enabled electrocardiogram, J Am Coll Cardiol, 75, 722, 10.1016/j.jacc.2019.12.030 Oh, 2018, Automated diagnosis of arrhythmia using combination of CNN and LSTM techniques with variable length heart beats, Comput Biol Med, 102, 278, 10.1016/j.compbiomed.2018.06.002 Mori, 2021, Diagnosing atrial septal defect from electrocardiogram with deep learning, Pediatr Cardiol, 42, 1379, 10.1007/s00246-021-02622-0 Petmezas, 2021, Automated atrial fibrillation detection using a hybrid CNN-LSTM network on imbalanced ECG datasets, Biomed Signal Process Control, 63, 10.1016/j.bspc.2020.102194 Jone, 2022, Artificial intelligence in congenital heart disease, JACC Adv, 1, 10.1016/j.jacadv.2022.100153 Goto, 2022, Multinational federated learning approach to train ECG and echocardiogram models for hypertrophic cardiomyopathy detection, Circulation, 146, 755, 10.1161/CIRCULATIONAHA.121.058696 Yagi, 2022, Importance of external validation and subgroup analysis of artificial intelligence in the detection of low ejection fraction from electrocardiograms, Eur Heart J Digit Health, 3, 654, 10.1093/ehjdh/ztac065 Marelli, 2014, Lifetime prevalence of congenital heart disease in the general population from 2000 to 2010, Circulation, 130, 749, 10.1161/CIRCULATIONAHA.113.008396