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

利用ACL损伤生物力学和神经肌肉风险特征分析来确定神经肌肉训练的有效性

阅读:1

Abstract

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/HYPOTHESIS: 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. STUDY DESIGN: Controlled laboratory study. METHODS: 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). CONCLUSION: 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. STUDY REGISTRATION: ClinicalTrials.gov NCT identifier: NCT01034527.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。