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首页> 外文期刊>Sports medicine >Factors Influencing the Relationship Between the Functional Movement Screen and Injury Risk in Sporting Populations: A Systematic Review and Meta-analysis
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Factors Influencing the Relationship Between the Functional Movement Screen and Injury Risk in Sporting Populations: A Systematic Review and Meta-analysis

机译:影响体育群体功能运动筛网与伤害风险关系的因素:系统评价和荟萃分析

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摘要

Background Studies investigating the association between the Functional Movement Screen (FMS) and sports injury risk have reported mixed results across a range of athlete populations. Objectives The purpose of this systematic review was to identify whether athlete age, sex, sport type, injury definition and mechanism contribute to the variable findings. Study design Systematic review and meta-analysis. Methods A systematic search was conducted in October 2018 using PubMed, EBSCOhost, Scopus, EmBase and Web of Science databases. Studies were included if they were peer reviewed and published in English language, included athletes from any competition level, performed the FMS at baseline to determine risk groups based on FMS composite score, asymmetry or pain, and prospectively observed injury incidence during training and competition. Study eligibility assessment and data extraction was performed by two reviewers. Random effects meta-analyses were used to determine odds ratio (OR), sensitivity and specificity with 95% confidence intervals. Sub-group analyses were based on athlete age, sex, sport type, injury definition, and injury mechanism. Results Twenty-nine studies were included in the FMS composite score meta-analysis. There was a smaller effect for junior (OR = 1.03 [0.67-1.59]; p = 0.881) compared to senior athletes (OR = 1.80 [1.17-2.78]; p = 0.008) and for male (OR = 1.79 [1.08-2.96]; p = 0.024) compared to female (OR = 1.92 [0.43-8.56]; p = 0.392) athletes. FMS composite scores were most likely to be associated with increased injury risk in rugby (OR = 5.92 [1.67-20.92]; p = 0.006), and to a lesser extent American football (OR = 4.41 [0.94-20.61]; p = 0.059) and ice hockey (OR = 3.70 [0.89-15.42]; p = 0.072), compared to other sports. Specificity values were higher than sensitivity values for FMS composite score. Eleven studies were included in the FMS asymmetry meta-analysis with insufficient study numbers to generate sport type subgroups. There was a larger effect for senior (OR = 1.78 [1.16-2.73]; p = 0.008) compared to junior athletes (OR = 1.21 [0.75-1.96]; p = 0.432). Sensitivity values were higher than specificity values for FMS asymmetry. For all FMS outcomes, there were minimal differences across injury definitions and mechanisms. Only four studies provided information about FMS pain and injury risk. There was a smaller effect for senior athletes (OR = 1.28 [0.33-4.96]; p = 0.723) compared to junior athletes (OR = 1.71 [1.16-2.50]; p = 0.006). Specificity values were higher than sensitivity values for FMS pain. Conclusion Athlete age, sex and sport type explained some of the variable findings of FMS prospective injury-risk studies. FMS composite scores and asymmetry were more useful for estimating injury risk in senior compared to junior athletes. Effect sizes tended to be small except for FMS composite scores in rugby, ice hockey and American football athletes.
机译:背景技术研究功能运动筛网(FMS)和运动损伤风险之间的关联已经报告了一系列运动员人口的混合结果。目的这一系统审查的目的是确定运动员年龄,性别,运动类型,伤害定义和机制是否有助于变量调查结果。研究设计系统评论和荟萃分析。方法使用PubMed,EBSCoHost,Scopus,Embase和Science Sandase进行系统搜索,在2018年10月进行了系统搜索。包括研究,如果他们以英语审查和发表的同行,其中包括任何竞争水平的运动员,在基线上进行了FMS,以根据FMS综合评分,不对称或疼痛确定风险群体,并在培训和竞争期间预期观察伤害发病。研究资格评估和数据提取由两位审稿人进行。随机效应META分析用于确定具有95%置信区间的差距(或),敏感性和特异性。小组分析基于运动员年龄,性别,运动类型,伤害定义和伤害机制。结果FMS复合成绩荟萃分析中包括29项研究。与高级运动员相比,初级(或= 1.03 [0.67-1.59]的初级(或= 1.03 [0.881)效果较小(或= 1.80 [1.17-2.78]; p = 0.008)和男性(或= 1.79 [1.08-2.96) ]; p = 0.024)与雌性相比(或= 1.92 [0.43-8.56]; P = 0.392)运动员。 FMS综合评分最有可能与橄榄球的损伤风险增加(或= 5.92 [1.67-20.92]; p = 0.006),以及较小程度的美国足球(或= 4.41 [0.94-20.61]; p = 0.059 )和冰球(或= 3.70 [0.89-15.42]; p = 0.072),与其他运动相比。特异性值高于FMS综合评分的灵敏度值。通过不足的研究编号,将11研究包括在FMS不对称间荟萃分析中,以产生运动型亚组。与初级运动员(或= 1.21 [0.75-1.96]相比,高级(或= 1.78 [1.16-2.73]; P = 0.008)效果较大(或= 1.21 [0.75-1.96]; p = 0.432)。灵敏度值高于FMS不对称的特异性值。对于所有FMS结果,伤害定义和机制差异很小。只有四项研究提供了有关FMS疼痛和伤害风险的信息。与初级运动员相比,高级运动员(或= 1.28 [0.33-4.96]效果较小(或= 1.28 [0.723)(或= 1.71 [1.16-2.50]; p = 0.006)。特异性值高于FMS疼痛的灵敏度值。结论运动员年龄,性别和运动类型解释了FMS前瞻性伤害风险研究的一些可变结果。与初级运动员相比,FMS综合评分和不对称对于估算高级伤害风险更有用。除了橄榄球,冰球和美式足球运动员的FMS综合评分外,效果尺寸趋于小。

著录项

  • 来源
    《Sports medicine》 |2019年第9期|共15页
  • 作者单位

    Univ South Australia Int Ctr Allied Hlth Evidence iCAHE GPO Box 2471 Adelaide SA 5000 Australia;

    Univ Sydney Fac Hlth Sci Exercise &

    Sport Sci Sydney NSW Australia;

    Univ South Australia Int Ctr Allied Hlth Evidence iCAHE GPO Box 2471 Adelaide SA 5000 Australia;

    Macquarie Univ Fac Med &

    Hlth Sci Sydney NSW Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 运动医学;
  • 关键词

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