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For: Loutfi M, Nawar M, Eltahan S, Elhoda AA. Predictors of response to cardiac resynchronization therapy in chronic heart failure patients. Egypt Heart J 2016. [DOI: 10.1016/j.ehj.2016.01.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]  Open
Number Cited by Other Article(s)
1
Neves Pereira MT, Tinoco M, Castro M, Pinheiro L, Cardoso F, Calvo L, Ribeiro S, Monteiro V, Sanfins V, Lourenço A. Assessing cardiac resynchronization therapy response in heart failure patients: a comparative analysis of efficacy and outcomes between transvenous and epicardial leads. Monaldi Arch Chest Dis 2024. [PMID: 38332712 DOI: 10.4081/monaldi.2024.2845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 01/23/2024] [Indexed: 02/10/2024]  Open
2
Electrocardiographic markers of cardiac resynchronization therapy response: delayed time to intrinsicoid deflection onset in lateral leads. J Geriatr Cardiol 2022;19:21-30. [PMID: 35233220 PMCID: PMC8832045 DOI: 10.11909/j.issn.1671-5411.2022.01.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]  Open
3
Nejadeh M, Bayat P, Kheirkhah J, Moladoust H. Predicting the response to cardiac resynchronization therapy (CRT) using the deep learning approach. Biocybern Biomed Eng 2021. [DOI: 10.1016/j.bbe.2021.05.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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