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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9572878 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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