Heart Rate Fragmentation: A New Approach to the Analysis of Cardiac Interbeat Interval Dynamics

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Heart Rate Fragmentation: A New Approach to the Analysis of Cardiac Interbeat Interval Dynamics

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dc.contributor.author Costa, Madalena D. en_US
dc.contributor.author Davis, Roger B. en_US
dc.contributor.author Goldberger, Ary L. en_US
dc.date.accessioned 2017-06-15T18:31:57Z
dc.date.issued 2017 en_US
dc.identifier.citation Costa, Madalena D., Roger B. Davis, and Ary L. Goldberger. 2017. “Heart Rate Fragmentation: A New Approach to the Analysis of Cardiac Interbeat Interval Dynamics.” Frontiers in Physiology 8 (1): 255. doi:10.3389/fphys.2017.00255. http://dx.doi.org/10.3389/fphys.2017.00255. en
dc.identifier.issn en
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:33030028
dc.description.abstract Background: Short-term heart rate variability (HRV) is most commonly attributed to physiologic vagal tone modulation. However, with aging and cardiovascular disease, the emergence of high short-term HRV, consistent with the breakdown of the neuroautonomic-electrophysiologic control system, may confound traditional HRV analysis. An apparent dynamical signature of such anomalous short-term HRV is frequent changes in heart rate acceleration sign, defined here as heart rate fragmentation. Objective: The aims were to: (1) introduce a set of metrics designed to probe the degree of sinus rhythm fragmentation; (2) test the hypothesis that the degree of fragmentation of heartbeat time series increases with the participants' age in a group of healthy subjects; (3) test the hypothesis that the heartbeat time series from patients with advanced coronary artery disease (CAD) are more fragmented than those from healthy subjects; and (4) compare the performance of the new fragmentation metrics with standard time and frequency domain measures of short-term HRV. Methods: We analyzed annotated, open-access Holter recordings (University of Rochester Holter Warehouse) from healthy subjects and patients with CAD using these newly introduced metrics of heart rate fragmentation, as well as standard time and frequency domain indices of short-term HRV, detrended fluctuation analysis and sample entropy. Results: The degree of fragmentation of cardiac interbeat interval time series increased significantly as a function of age in the healthy population as well as in patients with CAD. Fragmentation was higher for the patients with CAD than the healthy subjects. Heart rate fragmentation metrics outperformed traditional short-term HRV indices, as well as two widely used nonlinear measures, sample entropy and detrended fluctuation analysis short-term exponent, in distinguishing healthy subjects and patients with CAD. The same level of discrimination was obtained from the analysis of normal-to-normal sinus (NN) and cardiac interbeat interval (RR) time series. Conclusion: The fragmentation framework and accompanying metrics introduced here constitute a new way of assessing short-term HRV under free-running conditions, one which appears to overcome salient limitations of traditional HRV analysis. Fragmentation of sinus rhythm cadence may provide new dynamical biomarkers for probing the integrity of the neuroautonomic-electrophysiologic network controlling the heartbeat in health and disease. en
dc.language.iso en_US en
dc.publisher Frontiers Media S.A. en
dc.relation.isversionof doi:10.3389/fphys.2017.00255 en
dc.relation.hasversion http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5422439/pdf/ en
dash.license LAA en_US
dc.subject aging en
dc.subject coronary artery disease en
dc.subject fragmentation index en
dc.subject heart rate variability en
dc.subject vagal tone en
dc.title Heart Rate Fragmentation: A New Approach to the Analysis of Cardiac Interbeat Interval Dynamics en
dc.type Journal Article en_US
dc.description.version Version of Record en
dc.relation.journal Frontiers in Physiology en
dash.depositing.author Costa, Madalena D. en_US
dc.date.available 2017-06-15T18:31:57Z

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