Literature DB >> 34871963

Electrocardiographic biosignals to predict atrial fibrillation: Are we there yet?

Anthony H Kashou1, Peter A Noseworthy2.   

Abstract

The prevalence of atrial fibrillation (AF) continues to grow in an aging population, and its impact on both patients and the health care system has has made it a global burden. There are limited available options to detect individuals at risk of AF that may benefit from prevention and treatment strategies. The ECG may be an effective tool do so. In this work, we discuss the latest work by Hayiroğlu and colleagues related to this work and the use of novel ECG prediction tools to identify individuals individuals that could benefit from early and proactive screening, surveillance, and management strategies.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; Atrial cardiopathy; Atrial fibrillation; ECG; Electrocardiogram; Interatrial block; Ischemic stroke; Machine learning

Mesh：

Year:  2021        PMID： 34871963      PMCID： PMC8919434          DOI： 10.1016/j.jelectrocard.2021.11.033

Source DB:  PubMed          Journal:  J Electrocardiol        ISSN： 0022-0736            Impact factor:   1.438


  11 in total

1.  The AtRial Cardiopathy and Antithrombotic Drugs In prevention After cryptogenic stroke randomized trial: Rationale and methods.

Authors:  Hooman Kamel; W T Longstreth; David L Tirschwell; Richard A Kronmal; Joseph P Broderick; Yuko Y Palesch; Caitlyn Meinzer; Catherine Dillon; Irene Ewing; Judith A Spilker; Marco R Di Tullio; Eldad A Hod; Elsayed Z Soliman; Seemant Chaturvedi; Claudia S Moy; Scott Janis; Mitchell Sv Elkind
Journal:  Int J Stroke       Date:  2018-09-10       Impact factor: 5.266

2.  New electrocardiographic score for the prediction of atrial fibrillation: The MVP ECG risk score (morphology-voltage-P-wave duration).

Authors:  Bryce Alexander; Julia Milden; Bachar Hazim; Sohaib Haseeb; Antoni Bayes-Genis; Roberto Elosua; Manuel Martínez-Sellés; Cynthia Yeung; Wilma Hopman; Antoni Bayes de Luna; Adrian Baranchuk
Journal:  Ann Noninvasive Electrocardiol       Date:  2019-06-11       Impact factor: 1.468

3.  Electromechanical dysfunction of the left atrium associated with interatrial block.

Authors:  S B Goyal; D H Spodick
Journal:  Am Heart J       Date:  2001-11       Impact factor: 4.749

4.  Impact of atrial fibrillation on mortality, stroke, and medical costs.

Authors:  P A Wolf; J B Mitchell; C S Baker; W B Kannel; R B D'Agostino
Journal:  Arch Intern Med       Date:  1998-02-09

5.  ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation.

Authors:  Shaan Khurshid; Samuel Friedman; Christopher Reeder; Paolo Di Achille; Nathaniel Diamant; Pulkit Singh; Lia X Harrington; Xin Wang; Mostafa A Al-Alusi; Gopal Sarma; Andrea S Foulkes; Patrick T Ellinor; Christopher D Anderson; Jennifer E Ho; Anthony A Philippakis; Puneet Batra; Steven A Lubitz
Journal:  Circulation       Date:  2021-11-08       Impact factor: 29.690

6.  The significance of the morphology-voltage-P-wave duration (MVP) ECG score for prediction of in-hospital and long-term atrial fibrillation in ischemic stroke.

Authors:  Mert İlker Hayıroğlu; Tufan Çınar; Murat Selçuk; Göksel Çinier; Bryce Alexander; Selami Doğan; Vedat Çiçek; Şahhan Kılıç; Mert Murat Atmaca; Ahmet Lütfullah Orhan; Adrian Baranchuk
Journal:  J Electrocardiol       Date:  2021-09-14       Impact factor: 1.438

7.  An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction.

Authors:  Zachi I Attia; Peter A Noseworthy; Francisco Lopez-Jimenez; Samuel J Asirvatham; Abhishek J Deshmukh; Bernard J Gersh; Rickey E Carter; Xiaoxi Yao; Alejandro A Rabinstein; Brad J Erickson; Suraj Kapa; Paul A Friedman
Journal:  Lancet       Date:  2019-08-01       Impact factor: 79.321

8.  Cryptogenic stroke and underlying atrial fibrillation.

Authors:  Tommaso Sanna; Hans-Christoph Diener; Rod S Passman; Vincenzo Di Lazzaro; Richard A Bernstein; Carlos A Morillo; Marilyn Mollman Rymer; Vincent Thijs; Tyson Rogers; Frank Beckers; Kate Lindborg; Johannes Brachmann
Journal:  N Engl J Med       Date:  2014-06-26       Impact factor: 91.245

9.  Electrocardiographic biomarkers to predict atrial fibrillation in sinus rhythm electrocardiograms.

Authors:  Guillermo Jose Ortega; Jesus Jimenez-Borreguero; Ancor Sanz-García; Alberto Cecconi; Alberto Vera; Juan Miguel Camarasaltas; Fernando Alfonso
Journal:  Heart       Date:  2021-06-04       Impact factor: 5.994

10.  Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation-Related Stroke.

Authors:  Sushravya Raghunath; John M Pfeifer; Brandon K Fornwalt; Christopher M Haggerty; Alvaro E Ulloa-Cerna; Arun Nemani; Tanner Carbonati; Linyuan Jing; David P vanMaanen; Dustin N Hartzel; Jeffery A Ruhl; Braxton F Lagerman; Daniel B Rocha; Nathan J Stoudt; Gargi Schneider; Kipp W Johnson; Noah Zimmerman; Joseph B Leader; H Lester Kirchner; Christoph J Griessenauer; Ashraf Hafez; Christopher W Good
Journal:  Circulation       Date:  2021-02-16       Impact factor: 29.690
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