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A Novel Metric “Exercise Cardiac Load” Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes

Current metrics like baseline heart rate (HR) and HR recovery fail in predicting overtraining (OT), a syndrome manifesting from a deteriorating autonomic nervous system (ANS). Preventing OT requires tracking the influence of internal physiological loads induced by exercise training programs on the A...

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Autores principales: Wittels, S. Howard, Renaghan, Eric, Wishon, Michael Joseph, Wittels, Harrison L., Chong, Stephanie, Wittels, Eva Danielle, Hendricks, Stephanie, Hecocks, Dustin, Bellamy, Kyle, Girardi, Joe, Lee, Stephen, Vo, Tri, McDonald, Samantha M., Feigenbaum, Luis A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594468/
https://www.ncbi.nlm.nih.gov/pubmed/37873902
http://dx.doi.org/10.3390/jfmk8040143
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author Wittels, S. Howard
Renaghan, Eric
Wishon, Michael Joseph
Wittels, Harrison L.
Chong, Stephanie
Wittels, Eva Danielle
Hendricks, Stephanie
Hecocks, Dustin
Bellamy, Kyle
Girardi, Joe
Lee, Stephen
Vo, Tri
McDonald, Samantha M.
Feigenbaum, Luis A.
author_facet Wittels, S. Howard
Renaghan, Eric
Wishon, Michael Joseph
Wittels, Harrison L.
Chong, Stephanie
Wittels, Eva Danielle
Hendricks, Stephanie
Hecocks, Dustin
Bellamy, Kyle
Girardi, Joe
Lee, Stephen
Vo, Tri
McDonald, Samantha M.
Feigenbaum, Luis A.
author_sort Wittels, S. Howard
collection PubMed
description Current metrics like baseline heart rate (HR) and HR recovery fail in predicting overtraining (OT), a syndrome manifesting from a deteriorating autonomic nervous system (ANS). Preventing OT requires tracking the influence of internal physiological loads induced by exercise training programs on the ANS. Therefore, this study evaluated the predictability of a novel, exercise cardiac load metric on the deterioration of the ANS. Twenty male American football players, with an average age of 21.3 years and body mass indices ranging from 23.7 to 39.2 kg/m(2) were included in this study. Subjects participated in 40 strength- and power-focused exercise sessions over 8 weeks and wore armband monitors (Warfighter Monitor, Tiger Tech Solutions) equipped with electrocardiography capabilities. Exercise cardiac load was the product of average training HR and duration. Baseline HR, HR variability (HRV), average HR, and peak HR were also measured. HR recovery was measured on the following day. HRV indices assessed included the standard deviation of NN intervals (SDNN) and root mean square of successive RR interval differences (rMSSD) Linear regression models assessed the relationships between each cardiac metric and HR recovery, with statistical significance set at α < 0.05. Subjects were predominantly non-Hispanic black (70%) and aged 21.3 (±1.4) years. Adjusted models showed that exercise cardiac load elicited the strongest negative association with HR recovery for previous day (β = −0.18 ± 0.03; p < 0.0000), one-week (β = −0.20 ± 0.03; p < 0.0000) and two-week (β = −0.26 ± 0.03; p < 0.0000) training periods compared to average HR (βetas: −0.09 to −0.02; p < 0.0000) and peak HR (βetas: −0.13 to −0.23; p < 0.0000). Statistically significant relationships were also found for baseline HR (p < 0.0000), SDNN (p < 0.0000) and rMSSD (p < 0.0000). Exercise cardiac load appears to best predict ANS deterioration across one- to two-week training periods, showing a capability for tracking an athlete’s physiological tolerance and ANS response. Importantly, this information may increase the effectiveness of exercise training programs, enhance performance, and prevent OT.
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spelling pubmed-105944682023-10-25 A Novel Metric “Exercise Cardiac Load” Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes Wittels, S. Howard Renaghan, Eric Wishon, Michael Joseph Wittels, Harrison L. Chong, Stephanie Wittels, Eva Danielle Hendricks, Stephanie Hecocks, Dustin Bellamy, Kyle Girardi, Joe Lee, Stephen Vo, Tri McDonald, Samantha M. Feigenbaum, Luis A. J Funct Morphol Kinesiol Article Current metrics like baseline heart rate (HR) and HR recovery fail in predicting overtraining (OT), a syndrome manifesting from a deteriorating autonomic nervous system (ANS). Preventing OT requires tracking the influence of internal physiological loads induced by exercise training programs on the ANS. Therefore, this study evaluated the predictability of a novel, exercise cardiac load metric on the deterioration of the ANS. Twenty male American football players, with an average age of 21.3 years and body mass indices ranging from 23.7 to 39.2 kg/m(2) were included in this study. Subjects participated in 40 strength- and power-focused exercise sessions over 8 weeks and wore armband monitors (Warfighter Monitor, Tiger Tech Solutions) equipped with electrocardiography capabilities. Exercise cardiac load was the product of average training HR and duration. Baseline HR, HR variability (HRV), average HR, and peak HR were also measured. HR recovery was measured on the following day. HRV indices assessed included the standard deviation of NN intervals (SDNN) and root mean square of successive RR interval differences (rMSSD) Linear regression models assessed the relationships between each cardiac metric and HR recovery, with statistical significance set at α < 0.05. Subjects were predominantly non-Hispanic black (70%) and aged 21.3 (±1.4) years. Adjusted models showed that exercise cardiac load elicited the strongest negative association with HR recovery for previous day (β = −0.18 ± 0.03; p < 0.0000), one-week (β = −0.20 ± 0.03; p < 0.0000) and two-week (β = −0.26 ± 0.03; p < 0.0000) training periods compared to average HR (βetas: −0.09 to −0.02; p < 0.0000) and peak HR (βetas: −0.13 to −0.23; p < 0.0000). Statistically significant relationships were also found for baseline HR (p < 0.0000), SDNN (p < 0.0000) and rMSSD (p < 0.0000). Exercise cardiac load appears to best predict ANS deterioration across one- to two-week training periods, showing a capability for tracking an athlete’s physiological tolerance and ANS response. Importantly, this information may increase the effectiveness of exercise training programs, enhance performance, and prevent OT. MDPI 2023-10-07 /pmc/articles/PMC10594468/ /pubmed/37873902 http://dx.doi.org/10.3390/jfmk8040143 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wittels, S. Howard
Renaghan, Eric
Wishon, Michael Joseph
Wittels, Harrison L.
Chong, Stephanie
Wittels, Eva Danielle
Hendricks, Stephanie
Hecocks, Dustin
Bellamy, Kyle
Girardi, Joe
Lee, Stephen
Vo, Tri
McDonald, Samantha M.
Feigenbaum, Luis A.
A Novel Metric “Exercise Cardiac Load” Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes
title A Novel Metric “Exercise Cardiac Load” Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes
title_full A Novel Metric “Exercise Cardiac Load” Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes
title_fullStr A Novel Metric “Exercise Cardiac Load” Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes
title_full_unstemmed A Novel Metric “Exercise Cardiac Load” Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes
title_short A Novel Metric “Exercise Cardiac Load” Proposed to Track and Predict the Deterioration of the Autonomic Nervous System in Division I Football Athletes
title_sort novel metric “exercise cardiac load” proposed to track and predict the deterioration of the autonomic nervous system in division i football athletes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594468/
https://www.ncbi.nlm.nih.gov/pubmed/37873902
http://dx.doi.org/10.3390/jfmk8040143
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