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Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents

OBJECTIVE: To analyze whether the algorithm used for the heart rate variability assessment (fast Fourier transform versus autoregressive methods) influenced its association with cardiovascular risk factors in male adolescents. METHODS: This cross-sectional study included 1,152 male adolescents (aged...

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Autores principales: Soares, Antonio Henrique Germano, Farah, Breno Quintella, Cucato, Gabriel Grizzo, Bastos, Carmelo José Albanez, Christofaro, Diego Giulliano Destro, Vanderlei, Luiz Carlos Marques, Lima, Aluísio Henrique Rodrigues de Andrade, Ritti-Dias, Raphael Mendes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Instituto Israelita de Ensino e Pesquisa Albert Einstein 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4943353/
https://www.ncbi.nlm.nih.gov/pubmed/27462893
http://dx.doi.org/10.1590/S1679-45082016AO3683
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author Soares, Antonio Henrique Germano
Farah, Breno Quintella
Cucato, Gabriel Grizzo
Bastos, Carmelo José Albanez
Christofaro, Diego Giulliano Destro
Vanderlei, Luiz Carlos Marques
Lima, Aluísio Henrique Rodrigues de Andrade
Ritti-Dias, Raphael Mendes
author_facet Soares, Antonio Henrique Germano
Farah, Breno Quintella
Cucato, Gabriel Grizzo
Bastos, Carmelo José Albanez
Christofaro, Diego Giulliano Destro
Vanderlei, Luiz Carlos Marques
Lima, Aluísio Henrique Rodrigues de Andrade
Ritti-Dias, Raphael Mendes
author_sort Soares, Antonio Henrique Germano
collection PubMed
description OBJECTIVE: To analyze whether the algorithm used for the heart rate variability assessment (fast Fourier transform versus autoregressive methods) influenced its association with cardiovascular risk factors in male adolescents. METHODS: This cross-sectional study included 1,152 male adolescents (aged 14 to 19 years). The low frequency, high frequency components (absolute numbers and normalized units), low frequency/high frequency ratio, and total power of heart rate variability parameters were obtained using the fast Fourier transform and autoregressive methods, while the adolescents were resting in a supine position. RESULTS: All heart rate variability parameters calculated from both methods were different (p<0.05). However, a low effect size (<0.1) was found for all parameters. The intra-class correlation between methods ranged from 0.96 to 0.99, whereas the variation coefficient ranged from 7.4 to 14.8%. Furthermore, waist circumference was negatively associated with high frequency, and positively associated with low frequency and sympatovagal balance (p<0.001 for both fast Fourier transform and autoregressive methods in all associations). Systolic blood pressure was negatively associated with total power and high frequency, whereas it was positively associated with low frequency and sympatovagal balance (p<0.001 for both fast Fourier transform and autoregressive methods in all associations). Body mass index was negatively associated with high frequency, while it was positively associated with low frequency and sympatovagal balance (p values ranged from <0.001 to 0.007). CONCLUSION: There are significant differences in heart rate variability parameters obtained with the fast Fourier transform and autoregressive methods in male adolescent; however, these differences are not clinically significant.
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spelling pubmed-49433532016-08-10 Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents Soares, Antonio Henrique Germano Farah, Breno Quintella Cucato, Gabriel Grizzo Bastos, Carmelo José Albanez Christofaro, Diego Giulliano Destro Vanderlei, Luiz Carlos Marques Lima, Aluísio Henrique Rodrigues de Andrade Ritti-Dias, Raphael Mendes Einstein (Sao Paulo) Original Article OBJECTIVE: To analyze whether the algorithm used for the heart rate variability assessment (fast Fourier transform versus autoregressive methods) influenced its association with cardiovascular risk factors in male adolescents. METHODS: This cross-sectional study included 1,152 male adolescents (aged 14 to 19 years). The low frequency, high frequency components (absolute numbers and normalized units), low frequency/high frequency ratio, and total power of heart rate variability parameters were obtained using the fast Fourier transform and autoregressive methods, while the adolescents were resting in a supine position. RESULTS: All heart rate variability parameters calculated from both methods were different (p<0.05). However, a low effect size (<0.1) was found for all parameters. The intra-class correlation between methods ranged from 0.96 to 0.99, whereas the variation coefficient ranged from 7.4 to 14.8%. Furthermore, waist circumference was negatively associated with high frequency, and positively associated with low frequency and sympatovagal balance (p<0.001 for both fast Fourier transform and autoregressive methods in all associations). Systolic blood pressure was negatively associated with total power and high frequency, whereas it was positively associated with low frequency and sympatovagal balance (p<0.001 for both fast Fourier transform and autoregressive methods in all associations). Body mass index was negatively associated with high frequency, while it was positively associated with low frequency and sympatovagal balance (p values ranged from <0.001 to 0.007). CONCLUSION: There are significant differences in heart rate variability parameters obtained with the fast Fourier transform and autoregressive methods in male adolescent; however, these differences are not clinically significant. Instituto Israelita de Ensino e Pesquisa Albert Einstein 2016 /pmc/articles/PMC4943353/ /pubmed/27462893 http://dx.doi.org/10.1590/S1679-45082016AO3683 Text en http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Soares, Antonio Henrique Germano
Farah, Breno Quintella
Cucato, Gabriel Grizzo
Bastos, Carmelo José Albanez
Christofaro, Diego Giulliano Destro
Vanderlei, Luiz Carlos Marques
Lima, Aluísio Henrique Rodrigues de Andrade
Ritti-Dias, Raphael Mendes
Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents
title Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents
title_full Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents
title_fullStr Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents
title_full_unstemmed Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents
title_short Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents
title_sort is the algorithm used to process heart rate variability data clinically relevant? analysis in male adolescents
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4943353/
https://www.ncbi.nlm.nih.gov/pubmed/27462893
http://dx.doi.org/10.1590/S1679-45082016AO3683
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