Hewett, Am J Sports Med 2016 - Utilization of ACL Injury Biomechanical and Neuromuscular Risk Profile Analysis to Determine the Effectiveness of Neuromuscular Training - Article Summary

Utilization of ACL Injury Biomechanical and Neuromuscular Risk Profile Analysis to Determine the Effectiveness of Neuromuscular Training

Hewett, Myer, et al.·Am J Sports Med·2016·67 citations·Prospective cohort

Background

The widespread use of anterior cruciate ligament (ACL) injury prevention interventions has not been effective in reducing the injury incidence among female athletes who participate in high-risk sports.

Purpose

The purpose of this study was to determine if biomechanical and neuromuscular factors that contribute to the knee abduction moment (KAM), a predictor of future ACL injuries, could be used to characterize athletes by a distinct factor. Specifically, we hypothesized that a priori selected biomechanical and neuromuscular factors would characterize participants into distinct at-risk profiles.

Methods

Study Design: Controlled laboratory study.

A total of 624 female athletes who participated in jumping, cutting, and pivoting sports underwent testing before their competitive season.
During testing, athletes performed drop-jump tasks from which biomechanical measures were captured.
Using data from these tasks, latent profile analysis (LPA) was conducted to identify distinct profiles based on preintervention biomechanical and neuromuscular measures.
As a validation, we examined whether the profile membership was a significant predictor of the KAM.

Results

LPA using 6 preintervention biomechanical measures selected a priori resulted in 3 distinct profiles, including a low (profile 1), moderate (profile 2), and high (profile 3) risk for ACL injuries.
Athletes with profiles 2 and 3 had a significantly higher KAM compared with those with profile 1 (P < .05).

Conclusions

This is the first study to use LPA of biomechanical landing data to create ACL injury risk profiles. Three distinct risk groups were identified based on differences in the peak KAM.

Clinical Relevance: These findings demonstrate the existence of discernable groups of athletes that may benefit from injury prevention interventions.

Supplemental

Utilization of ACL Injury Biomechanical and Neuromuscular Risk Profile Analysis to Determine the Effectiveness of Neuromuscular Training

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Utilization of ACL Injury Biomechanical and Neuromuscular Risk Profile Analysis to Determine the Effectiveness of Neuromuscular Training

Hewett, Myer, et al.·Am J Sports Med·2016·67 citations·Prospective cohort

Free Full Text·DOI·PubMed

Background

Purpose

Methods

Study Design: Controlled laboratory study.

A total of 624 female athletes who participated in jumping, cutting, and pivoting sports underwent testing before their competitive season.
During testing, athletes performed drop-jump tasks from which biomechanical measures were captured.
Using data from these tasks, latent profile analysis (LPA) was conducted to identify distinct profiles based on preintervention biomechanical and neuromuscular measures.
As a validation, we examined whether the profile membership was a significant predictor of the KAM.

Results

LPA using 6 preintervention biomechanical measures selected a priori resulted in 3 distinct profiles, including a low (profile 1), moderate (profile 2), and high (profile 3) risk for ACL injuries.
Athletes with profiles 2 and 3 had a significantly higher KAM compared with those with profile 1 (P < .05).

Conclusions

This is the first study to use LPA of biomechanical landing data to create ACL injury risk profiles. Three distinct risk groups were identified based on differences in the peak KAM.

Clinical Relevance: These findings demonstrate the existence of discernable groups of athletes that may benefit from injury prevention interventions.

Background

Purpose

Methods

Study Design: Controlled laboratory study.

A total of 624 female athletes who participated in jumping, cutting, and pivoting sports underwent testing before their competitive season.
During testing, athletes performed drop-jump tasks from which biomechanical measures were captured.
Using data from these tasks, latent profile analysis (LPA) was conducted to identify distinct profiles based on preintervention biomechanical and neuromuscular measures.
As a validation, we examined whether the profile membership was a significant predictor of the KAM.

Results

LPA using 6 preintervention biomechanical measures selected a priori resulted in 3 distinct profiles, including a low (profile 1), moderate (profile 2), and high (profile 3) risk for ACL injuries.
Athletes with profiles 2 and 3 had a significantly higher KAM compared with those with profile 1 (P < .05).

Conclusions

This is the first study to use LPA of biomechanical landing data to create ACL injury risk profiles. Three distinct risk groups were identified based on differences in the peak KAM.

Clinical Relevance: These findings demonstrate the existence of discernable groups of athletes that may benefit from injury prevention interventions.

Background

Purpose

Methods

Study Design: Controlled laboratory study.

A total of 624 female athletes who participated in jumping, cutting, and pivoting sports underwent testing before their competitive season.
During testing, athletes performed drop-jump tasks from which biomechanical measures were captured.
Using data from these tasks, latent profile analysis (LPA) was conducted to identify distinct profiles based on preintervention biomechanical and neuromuscular measures.
As a validation, we examined whether the profile membership was a significant predictor of the KAM.

Results

LPA using 6 preintervention biomechanical measures selected a priori resulted in 3 distinct profiles, including a low (profile 1), moderate (profile 2), and high (profile 3) risk for ACL injuries.
Athletes with profiles 2 and 3 had a significantly higher KAM compared with those with profile 1 (P < .05).

Conclusions

This is the first study to use LPA of biomechanical landing data to create ACL injury risk profiles. Three distinct risk groups were identified based on differences in the peak KAM.

Clinical Relevance: These findings demonstrate the existence of discernable groups of athletes that may benefit from injury prevention interventions.