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IEEE transactions on bio-medical engineering v.64 no.2, 2017년, pp.302 - 309   SCI SCIE
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On the Influence of Heart Rate and Coupling Interval Prematurity on Heart Rate Turbulence

Barquero-Perez, Oscar (Signal Theory and Communications, Telematics and Computing DepartmentRey Juan Carlos University ) ; Figuera, Carlos (Signal Theory and Communications, Telematics and Computing DepartmentRey Juan Carlos University ) ; Goya-Esteban, Rebeca (Signal Theory and Communications, Telematics and Computing DepartmentRey Juan Carlos University ) ; Mora-Jimenez, Inmaculada (Signal Theory and Communications DepartmentMiguel Hernndez University ) ; Gimeno-Blanes, Francisco Javier (Biomedical Signal Interpretation and Computational Simulation Group, Aragón Institute of Engineering Research (I3A)IIS Aragón, Universidad de Zaragoza ) ; Laguna, Pablo (Biomedical Signal Interpretation and Computational Simulation Group, Aragón Institute of Engineering Research (I3A)IIS Aragón, Universidad de Zaragoza ) ; Martinez, Juan Pablo (Biomedical Signal Interpretation and Computational Simulation Group, Aragón Institute of Engineering Research (I3A)IIS Aragón, Universidad de Zaragoza ) ; Gil, Eduardo (Department of Biomedical Engineering and the Center of Integrative ElectrocardiologyLund University ) ; Sornmo, Leif (Arrhythmia UnitHospital Univers ) ; Garcia-Alberola, Arcadi ; Rojo-Alvarez, Jose Luis ;
  • 초록  

    Objective: Heart rate turbulence (HRT) has been successfully explored for cardiac risk stratification. While HRT is known to be influenced by the heart rate (HR) and the coupling interval (CI), nonconcordant results have been reported on how the CI influences HRT. The purpose of this study is to investigate HRT changes in terms of CI and HR by means of an especially designed protocol. Methods: A dataset was acquired from 11 patients with structurally normal hearts for which CI was altered by different pacing trains and HR by isoproterenol during electrophysiological study (EPS). The protocol was designed so that, first, the effect of HR changes on HRT and, second, the combined effect of HR and CI could be explored. As a complement to the EPS dataset, a database of 24-h Holters from 61 acute myocardial infarction (AMI) patients was studied for the purpose of assessing risk. Data analysis was performed by using different nonlinear ridge regression models, and the relevance of model variables was assessed using resampling methods. The EPS subjects, with and without isoproterenol, were analyzed separately. Results: The proposed nonlinear regression models were found to account for the influence of HR and CI on HRT, both in patients undergoing EPS without isoproterenol and in low-risk AMI patients, whereas this influence was absent in high-risk AMI patients. Moreover, model coefficients related to CI were not statistically significant, $p > 0.05$ , on EPS subjects with isoproterenol. Conclusion: The observed relationship between CI and HRT, being in agreement with the baroreflex hypothesis, was statistically significant ( $p ), when decoupling the effect of HR and normalizing the CI by the HR. Significance: The results of this study can help to provide new risk indicators that take into account physiological influence on HRT, as well as to model how this influence changes in different cardiac conditions.


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