运动员
医学
物理疗法
随机对照试验
前交叉韧带损伤
物理医学与康复
伤害预防
前交叉韧带
毒物控制
外科
急诊医学
作者
Mette Kreutzfeldt Zebis,Lars L. Andersen,Mikkel Brandt,Grethe Myklebust,Jesper Bencke,Hanne Bloch Lauridsen,Thomas Bandholm,Kristian Thorborg,Per Hölmich,Per Aagaard
标识
DOI:10.1136/bjsports-2015-094776
摘要
BACKGROUND: Adolescent female football and handball players are among the athletes with the highest risk of sustaining anterior cruciate ligament (ACL) injuries. AIM: This study evaluated the effects of evidence-based lower extremity injury prevention training on neuromuscular and biomechanical risk factors for non-contact ACL injury. METHODS: 40 adolescent female football and handball players (15-16 years) were randomly allocated to a control group (CON, n=20) or neuromuscular training group (NMT, n=20). The NMT group performed an injury prevention programme as a warm-up before their usual training 3 times weekly for 12 weeks. The CON group completed their regular warm-up exercise programme before training. Players were tested while performing a side cutting movement at baseline and 12-week follow-up, using surface electromyography (EMG) and three-dimensional movement analysis. We calculated: (1) EMG amplitude from vastus lateralis (VL), semitendinosus (ST) and biceps femoris 10 ms prior to initial contact (IC) normalised to peak EMG amplitude recorded during maximal voluntary isometric contraction and (2) VL-ST EMG preactivity difference during the 10 ms prior to foot contact (primary outcome). We measured maximal knee joint valgus moment and knee valgus angle at IC. RESULTS: There was a difference between groups at follow-up in VL-ST preactivity (43% between-group difference; 95% CI 32% to 55%). No between-group differences were observed for kinematic and kinetic variables. CONCLUSIONS: A 12-week injury prevention programme in addition to training and match play in adolescent females altered the pattern of agonist-antagonist muscle preactivity during side cutting. This may represent a more ACL-protective motor strategy.
科研通智能强力驱动
Strongly Powered by AbleSci AI