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Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects

The present study aimed at testing the hypothesis that application of multiscale cross-approximate entropy (MCAE) analysis in the study of nonlinear coupling behavior of two synchronized time series of different natures [i.e., R-R interval (RRI) and crest time (CT, the time interval from foot to pea...

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Autores principales: Xiao, Ming-Xia, Wei, Hai-Cheng, Xu, Ya-Jie, Wu, Hsien-Tsai, Sun, Cheuk-Kwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513023/
https://www.ncbi.nlm.nih.gov/pubmed/33265587
http://dx.doi.org/10.3390/e20070497
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author Xiao, Ming-Xia
Wei, Hai-Cheng
Xu, Ya-Jie
Wu, Hsien-Tsai
Sun, Cheuk-Kwan
author_facet Xiao, Ming-Xia
Wei, Hai-Cheng
Xu, Ya-Jie
Wu, Hsien-Tsai
Sun, Cheuk-Kwan
author_sort Xiao, Ming-Xia
collection PubMed
description The present study aimed at testing the hypothesis that application of multiscale cross-approximate entropy (MCAE) analysis in the study of nonlinear coupling behavior of two synchronized time series of different natures [i.e., R-R interval (RRI) and crest time (CT, the time interval from foot to peakof a pulse wave)] could yield information on complexity related to diabetes-associated vascular changes. Signals of a single waveform parameter (i.e., CT) from photoplethysmography and RRI from electrocardiogram were simultaneously acquired within a period of one thousand cardiac cycles for the computation of different multiscale entropy indices from healthy young adults (n = 22) (Group 1), upper-middle aged non-diabetic subjects (n = 34) (Group 2) and diabetic patients (n = 34) (Group 3). The demographic (i.e., age), anthropometric (i.e., body height, body weight, waist circumference, body-mass index), hemodynamic (i.e., systolic and diastolic blood pressures), and serum biochemical (i.e., high- and low-density lipoprotein cholesterol, total cholesterol, and triglyceride) parameters were compared with different multiscale entropy indices including small- and large-scale multiscale entropy indices for CT and RRI [MEI(SS)(CT), MEI(LS)(CT), MEI(SS)(RRI), MEI(LS)(RRI), respectively] as well as small- and large-scale multiscale cross-approximate entropy indices [MCEI(SS), MCEI(LS), respectively]. The results demonstrated that both MEI(LS)(RRI) and MCEI(LS) significantly differentiated between Group 2 and Group 3 (all p < 0.017). Multivariate linear regression analysis showed significant associations of MEI(LS)(RRI) and MCEI(LS)(RRI,CT) with age and glycated hemoglobin level (all p < 0.017). The findings highlight the successful application of a novel multiscale cross-approximate entropy index in non-invasively identifying diabetes-associated subtle changes in vascular functional integrity, which is of clinical importance in preventive medicine.
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spelling pubmed-75130232020-11-09 Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects Xiao, Ming-Xia Wei, Hai-Cheng Xu, Ya-Jie Wu, Hsien-Tsai Sun, Cheuk-Kwan Entropy (Basel) Article The present study aimed at testing the hypothesis that application of multiscale cross-approximate entropy (MCAE) analysis in the study of nonlinear coupling behavior of two synchronized time series of different natures [i.e., R-R interval (RRI) and crest time (CT, the time interval from foot to peakof a pulse wave)] could yield information on complexity related to diabetes-associated vascular changes. Signals of a single waveform parameter (i.e., CT) from photoplethysmography and RRI from electrocardiogram were simultaneously acquired within a period of one thousand cardiac cycles for the computation of different multiscale entropy indices from healthy young adults (n = 22) (Group 1), upper-middle aged non-diabetic subjects (n = 34) (Group 2) and diabetic patients (n = 34) (Group 3). The demographic (i.e., age), anthropometric (i.e., body height, body weight, waist circumference, body-mass index), hemodynamic (i.e., systolic and diastolic blood pressures), and serum biochemical (i.e., high- and low-density lipoprotein cholesterol, total cholesterol, and triglyceride) parameters were compared with different multiscale entropy indices including small- and large-scale multiscale entropy indices for CT and RRI [MEI(SS)(CT), MEI(LS)(CT), MEI(SS)(RRI), MEI(LS)(RRI), respectively] as well as small- and large-scale multiscale cross-approximate entropy indices [MCEI(SS), MCEI(LS), respectively]. The results demonstrated that both MEI(LS)(RRI) and MCEI(LS) significantly differentiated between Group 2 and Group 3 (all p < 0.017). Multivariate linear regression analysis showed significant associations of MEI(LS)(RRI) and MCEI(LS)(RRI,CT) with age and glycated hemoglobin level (all p < 0.017). The findings highlight the successful application of a novel multiscale cross-approximate entropy index in non-invasively identifying diabetes-associated subtle changes in vascular functional integrity, which is of clinical importance in preventive medicine. MDPI 2018-06-27 /pmc/articles/PMC7513023/ /pubmed/33265587 http://dx.doi.org/10.3390/e20070497 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xiao, Ming-Xia
Wei, Hai-Cheng
Xu, Ya-Jie
Wu, Hsien-Tsai
Sun, Cheuk-Kwan
Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects
title Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects
title_full Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects
title_fullStr Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects
title_full_unstemmed Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects
title_short Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects
title_sort combination of r-r interval and crest time in assessing complexity using multiscale cross-approximate entropy in normal and diabetic subjects
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513023/
https://www.ncbi.nlm.nih.gov/pubmed/33265587
http://dx.doi.org/10.3390/e20070497
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