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Whole-Body Reactive Agility Metrics to Identify Football Players With a Core and Lower Extremity Injury Risk

Clinical prediction models are useful in addressing several orthopedic conditions with various cohorts. American football provides a good population for attempting to predict injuries due to their relatively high injury rate. Physical performance can be assessed a variety of ways using an assortment...

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Autores principales: Bruce, Scott L., Wilkerson, Gary B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564038/
https://www.ncbi.nlm.nih.gov/pubmed/34746776
http://dx.doi.org/10.3389/fspor.2021.733567
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author Bruce, Scott L.
Wilkerson, Gary B.
author_facet Bruce, Scott L.
Wilkerson, Gary B.
author_sort Bruce, Scott L.
collection PubMed
description Clinical prediction models are useful in addressing several orthopedic conditions with various cohorts. American football provides a good population for attempting to predict injuries due to their relatively high injury rate. Physical performance can be assessed a variety of ways using an assortment of different tests to assess a diverse set of metrics, which may include reaction time, speed, acceleration, and deceleration. Asymmetry, the difference between right and left performance has been identified as a possible risk factor for injury. The purpose of this study was to determine the whole-body reactive agility metrics that would identify Division I football players who were at elevated risk for core, and lower extremity injuries (CLEI). This cohort study utilized 177 Division I football players with a total of 57 CLEI suffered who were baseline tested prior to the season. Single-task and dual-task whole-body reactive agility movements in lateral and diagonal direction reacting to virtual reality targets were analyzed separately. Receiver operator characteristic (ROC) analyses narrowed the 34 original predictor variables to five variables. Logistic regression analysis determined the three strongest predictors of CLEI for this cohort to be: lateral agility acceleration asymmetry, lateral flanker deceleration asymmetry, and diagonal agility reaction time average. Univariable analysis found odds ratios to range from 1.98 to 2.75 for these predictors of CLEI. ROC analysis had an area under the curve of 0.702 for any combination of two or more risk factors produced an odds ratio of 5.5 for risk of CLEI. These results suggest an asymmetry of 8–15% on two of the identified metrics or a slowed reaction time of ≥0.787 s places someone at increased risk of injury. Sixty-three percent (36/57) of the players who sustained an injury had ≥2 positive predictors In spite of the recognized limitation, these finding support the belief that whole-body reactive agility performance can identify Division I football players who are at elevated risk for CLEI.
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spelling pubmed-85640382021-11-04 Whole-Body Reactive Agility Metrics to Identify Football Players With a Core and Lower Extremity Injury Risk Bruce, Scott L. Wilkerson, Gary B. Front Sports Act Living Sports and Active Living Clinical prediction models are useful in addressing several orthopedic conditions with various cohorts. American football provides a good population for attempting to predict injuries due to their relatively high injury rate. Physical performance can be assessed a variety of ways using an assortment of different tests to assess a diverse set of metrics, which may include reaction time, speed, acceleration, and deceleration. Asymmetry, the difference between right and left performance has been identified as a possible risk factor for injury. The purpose of this study was to determine the whole-body reactive agility metrics that would identify Division I football players who were at elevated risk for core, and lower extremity injuries (CLEI). This cohort study utilized 177 Division I football players with a total of 57 CLEI suffered who were baseline tested prior to the season. Single-task and dual-task whole-body reactive agility movements in lateral and diagonal direction reacting to virtual reality targets were analyzed separately. Receiver operator characteristic (ROC) analyses narrowed the 34 original predictor variables to five variables. Logistic regression analysis determined the three strongest predictors of CLEI for this cohort to be: lateral agility acceleration asymmetry, lateral flanker deceleration asymmetry, and diagonal agility reaction time average. Univariable analysis found odds ratios to range from 1.98 to 2.75 for these predictors of CLEI. ROC analysis had an area under the curve of 0.702 for any combination of two or more risk factors produced an odds ratio of 5.5 for risk of CLEI. These results suggest an asymmetry of 8–15% on two of the identified metrics or a slowed reaction time of ≥0.787 s places someone at increased risk of injury. Sixty-three percent (36/57) of the players who sustained an injury had ≥2 positive predictors In spite of the recognized limitation, these finding support the belief that whole-body reactive agility performance can identify Division I football players who are at elevated risk for CLEI. Frontiers Media S.A. 2021-10-20 /pmc/articles/PMC8564038/ /pubmed/34746776 http://dx.doi.org/10.3389/fspor.2021.733567 Text en Copyright © 2021 Bruce and Wilkerson. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Sports and Active Living
Bruce, Scott L.
Wilkerson, Gary B.
Whole-Body Reactive Agility Metrics to Identify Football Players With a Core and Lower Extremity Injury Risk
title Whole-Body Reactive Agility Metrics to Identify Football Players With a Core and Lower Extremity Injury Risk
title_full Whole-Body Reactive Agility Metrics to Identify Football Players With a Core and Lower Extremity Injury Risk
title_fullStr Whole-Body Reactive Agility Metrics to Identify Football Players With a Core and Lower Extremity Injury Risk
title_full_unstemmed Whole-Body Reactive Agility Metrics to Identify Football Players With a Core and Lower Extremity Injury Risk
title_short Whole-Body Reactive Agility Metrics to Identify Football Players With a Core and Lower Extremity Injury Risk
title_sort whole-body reactive agility metrics to identify football players with a core and lower extremity injury risk
topic Sports and Active Living
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8564038/
https://www.ncbi.nlm.nih.gov/pubmed/34746776
http://dx.doi.org/10.3389/fspor.2021.733567
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