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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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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. |
format | Online Article Text |
id | pubmed-7513023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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