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Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis

This study aimed to evaluate the relationship between injury risk, acute load (AL), acute chronic workload ratio (ACWR) and a new proposed ACWR. Design: a retrospective cohort study of the year 2018 was conducted on Argentine first-division soccer players. Participants: Data from 35 players (age = 2...

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Autores principales: Carbone, Leandro, Sampietro, Matias, Cicognini, Agustin, García-Sillero, Manuel, Vargas-Molina, Salvador
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572878/
https://www.ncbi.nlm.nih.gov/pubmed/36233815
http://dx.doi.org/10.3390/jcm11195945
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author Carbone, Leandro
Sampietro, Matias
Cicognini, Agustin
García-Sillero, Manuel
Vargas-Molina, Salvador
author_facet Carbone, Leandro
Sampietro, Matias
Cicognini, Agustin
García-Sillero, Manuel
Vargas-Molina, Salvador
author_sort Carbone, Leandro
collection PubMed
description This study aimed to evaluate the relationship between injury risk, acute load (AL), acute chronic workload ratio (ACWR) and a new proposed ACWR. Design: a retrospective cohort study of the year 2018 was conducted on Argentine first-division soccer players. Participants: Data from 35 players (age = 26.7 ± 4.71 years; height = 176.28 ± 6.09 cm; mass = 74.2 ± 5.27 kg) were recorded; 12 players’ data were analyzed for 1 year, and 23 players’ data were analyzed for 6 months. Interventions: The mean difference of ACWR (MD = 0.22), high-density interval (HDI 95% = (0.07, 0.36)) and AL (MD = 449.23, HDI 95% = (146.41, 751.2)) between groups turned out to be statistically significant. The effect size between groups comparing ACWR and AL was identical (ES = 0.64). Results: The probability of suffering an injury conditioned by ACWR or random ACWR was similar for all estimated quantiles, and the differences between them were not statistically significant. Conclusions: The ACWR ratio, using internal load monitoring, is no better than a synthetic ACWR created from a random denominator to predict the probability of injury. ACWR should not be used in isolation to analyze the causality between load and injury.
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spelling pubmed-95728782022-10-17 Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis Carbone, Leandro Sampietro, Matias Cicognini, Agustin García-Sillero, Manuel Vargas-Molina, Salvador J Clin Med Article This study aimed to evaluate the relationship between injury risk, acute load (AL), acute chronic workload ratio (ACWR) and a new proposed ACWR. Design: a retrospective cohort study of the year 2018 was conducted on Argentine first-division soccer players. Participants: Data from 35 players (age = 26.7 ± 4.71 years; height = 176.28 ± 6.09 cm; mass = 74.2 ± 5.27 kg) were recorded; 12 players’ data were analyzed for 1 year, and 23 players’ data were analyzed for 6 months. Interventions: The mean difference of ACWR (MD = 0.22), high-density interval (HDI 95% = (0.07, 0.36)) and AL (MD = 449.23, HDI 95% = (146.41, 751.2)) between groups turned out to be statistically significant. The effect size between groups comparing ACWR and AL was identical (ES = 0.64). Results: The probability of suffering an injury conditioned by ACWR or random ACWR was similar for all estimated quantiles, and the differences between them were not statistically significant. Conclusions: The ACWR ratio, using internal load monitoring, is no better than a synthetic ACWR created from a random denominator to predict the probability of injury. ACWR should not be used in isolation to analyze the causality between load and injury. MDPI 2022-10-08 /pmc/articles/PMC9572878/ /pubmed/36233815 http://dx.doi.org/10.3390/jcm11195945 Text en © 2022 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
Carbone, Leandro
Sampietro, Matias
Cicognini, Agustin
García-Sillero, Manuel
Vargas-Molina, Salvador
Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis
title Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis
title_full Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis
title_fullStr Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis
title_full_unstemmed Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis
title_short Is the Relationship between Acute and Chronic Workload a Valid Predictive Injury Tool? A Bayesian Analysis
title_sort is the relationship between acute and chronic workload a valid predictive injury tool? a bayesian analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572878/
https://www.ncbi.nlm.nih.gov/pubmed/36233815
http://dx.doi.org/10.3390/jcm11195945
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