Fatigue shifts and scatters heart rate variability in elite endurance athletes.
<h4>Purpose</h4>This longitudinal study aimed at comparing heart rate variability (HRV) in elite athletes identified either in 'fatigue' or in 'no-fatigue' state in 'real life' conditions.<h4>Methods</h4>57 elite Nordic-skiers were surveyed over...
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oai:doaj.org-article:2b0ea9a0f9c64e7ba6fbd7dc69fb687b2021-11-18T09:00:08ZFatigue shifts and scatters heart rate variability in elite endurance athletes.1932-620310.1371/journal.pone.0071588https://doaj.org/article/2b0ea9a0f9c64e7ba6fbd7dc69fb687b2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23951198/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Purpose</h4>This longitudinal study aimed at comparing heart rate variability (HRV) in elite athletes identified either in 'fatigue' or in 'no-fatigue' state in 'real life' conditions.<h4>Methods</h4>57 elite Nordic-skiers were surveyed over 4 years. R-R intervals were recorded supine (SU) and standing (ST). A fatigue state was quoted with a validated questionnaire. A multilevel linear regression model was used to analyze relationships between heart rate (HR) and HRV descriptors [total spectral power (TP), power in low (LF) and high frequency (HF) ranges expressed in ms(2) and normalized units (nu)] and the status without and with fatigue. The variables not distributed normally were transformed by taking their common logarithm (log10).<h4>Results</h4>172 trials were identified as in a 'fatigue' and 891 as in 'no-fatigue' state. All supine HR and HRV parameters (Beta±SE) were significantly different (P<0.0001) between 'fatigue' and 'no-fatigue': HRSU (+6.27±0.61 bpm), logTPSU (-0.36±0.04), logLFSU (-0.27±0.04), logHFSU (-0.46±0.05), logLF/HFSU (+0.19±0.03), HFSU(nu) (-9.55±1.33). Differences were also significant (P<0.0001) in standing: HRST (+8.83±0.89), logTPST (-0.28±0.03), logLFST (-0.29±0.03), logHFST (-0.32±0.04). Also, intra-individual variance of HRV parameters was larger (P<0.05) in the 'fatigue' state (logTPSU: 0.26 vs. 0.07, logLFSU: 0.28 vs. 0.11, logHFSU: 0.32 vs. 0.08, logTPST: 0.13 vs. 0.07, logLFST: 0.16 vs. 0.07, logHFST: 0.25 vs. 0.14).<h4>Conclusion</h4>HRV was significantly lower in 'fatigue' vs. 'no-fatigue' but accompanied with larger intra-individual variance of HRV parameters in 'fatigue'. The broader intra-individual variance of HRV parameters might encompass different changes from no-fatigue state, possibly reflecting different fatigue-induced alterations of HRV pattern.Laurent SchmittJacques RegnardMaxime DesmaretsFréderic MaunyLaurent MourotJean-Pierre FouillotNicolas CoulmyGrégoire MilletPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 8, p e71588 (2013) |
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Medicine R Science Q Laurent Schmitt Jacques Regnard Maxime Desmarets Fréderic Mauny Laurent Mourot Jean-Pierre Fouillot Nicolas Coulmy Grégoire Millet Fatigue shifts and scatters heart rate variability in elite endurance athletes. |
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<h4>Purpose</h4>This longitudinal study aimed at comparing heart rate variability (HRV) in elite athletes identified either in 'fatigue' or in 'no-fatigue' state in 'real life' conditions.<h4>Methods</h4>57 elite Nordic-skiers were surveyed over 4 years. R-R intervals were recorded supine (SU) and standing (ST). A fatigue state was quoted with a validated questionnaire. A multilevel linear regression model was used to analyze relationships between heart rate (HR) and HRV descriptors [total spectral power (TP), power in low (LF) and high frequency (HF) ranges expressed in ms(2) and normalized units (nu)] and the status without and with fatigue. The variables not distributed normally were transformed by taking their common logarithm (log10).<h4>Results</h4>172 trials were identified as in a 'fatigue' and 891 as in 'no-fatigue' state. All supine HR and HRV parameters (Beta±SE) were significantly different (P<0.0001) between 'fatigue' and 'no-fatigue': HRSU (+6.27±0.61 bpm), logTPSU (-0.36±0.04), logLFSU (-0.27±0.04), logHFSU (-0.46±0.05), logLF/HFSU (+0.19±0.03), HFSU(nu) (-9.55±1.33). Differences were also significant (P<0.0001) in standing: HRST (+8.83±0.89), logTPST (-0.28±0.03), logLFST (-0.29±0.03), logHFST (-0.32±0.04). Also, intra-individual variance of HRV parameters was larger (P<0.05) in the 'fatigue' state (logTPSU: 0.26 vs. 0.07, logLFSU: 0.28 vs. 0.11, logHFSU: 0.32 vs. 0.08, logTPST: 0.13 vs. 0.07, logLFST: 0.16 vs. 0.07, logHFST: 0.25 vs. 0.14).<h4>Conclusion</h4>HRV was significantly lower in 'fatigue' vs. 'no-fatigue' but accompanied with larger intra-individual variance of HRV parameters in 'fatigue'. The broader intra-individual variance of HRV parameters might encompass different changes from no-fatigue state, possibly reflecting different fatigue-induced alterations of HRV pattern. |
format |
article |
author |
Laurent Schmitt Jacques Regnard Maxime Desmarets Fréderic Mauny Laurent Mourot Jean-Pierre Fouillot Nicolas Coulmy Grégoire Millet |
author_facet |
Laurent Schmitt Jacques Regnard Maxime Desmarets Fréderic Mauny Laurent Mourot Jean-Pierre Fouillot Nicolas Coulmy Grégoire Millet |
author_sort |
Laurent Schmitt |
title |
Fatigue shifts and scatters heart rate variability in elite endurance athletes. |
title_short |
Fatigue shifts and scatters heart rate variability in elite endurance athletes. |
title_full |
Fatigue shifts and scatters heart rate variability in elite endurance athletes. |
title_fullStr |
Fatigue shifts and scatters heart rate variability in elite endurance athletes. |
title_full_unstemmed |
Fatigue shifts and scatters heart rate variability in elite endurance athletes. |
title_sort |
fatigue shifts and scatters heart rate variability in elite endurance athletes. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2013 |
url |
https://doaj.org/article/2b0ea9a0f9c64e7ba6fbd7dc69fb687b |
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