Non-contact Anterior Cruciate Ligament Injury Epidemiology in Team-Ball Sports: A Systematic Review with Meta-analysis by Sex, Age, Sport, Participation Level, and Exposure Type,Sports Medicine

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Non-contact Anterior Cruciate Ligament Injury Epidemiology in Team-Ball Sports: A Systematic Review with Meta-analysis by Sex, Age, Sport, Participation Level, and Exposure Type
Sports Medicine ( IF 9.3 ) Pub Date : 2022-05-27 , DOI: 10.1007/s40279-022-01697-w
Lionel Chia _{1,

2} , Danilo De Oliveira Silva ₃ , Matthew Whalan _{4,

5} , Marnee J McKay ₁ , Justin Sullivan ₁ , Colin W Fuller ₆ , Evangelos Pappas _{1,

7}

Affiliation

Background

Not all anterior cruciate ligament (ACL) injuries are preventable. While some ACL injuries are unavoidable such as those resulting from a tackle, others that occur in non-contact situations like twisting and turning in the absence of external contact might be more preventable. Because ACL injuries commonly occur in team ball-sports that involve jumping, landing and cutting manoeuvres, accurate information about the epidemiology of non-contact ACL injuries in these sports is needed to quantify their extent and burden to guide resource allocation for risk-reduction efforts.

Objective

To synthesize the evidence on the incidence and proportion of non-contact to total ACL injuries by sex, age, sport, participation level and exposure type in team ball-sports.

Methods

Six databases (MEDLINE, EMBASE, Web of Science, CINAHL, Scopus and SPORTDiscus) were searched from inception to July 2021. Cohort studies of team ball-sports reporting number of knee injuries as a function of exposure and injury mechanism were included.

Results

Forty-five studies covering 13 team ball-sports were included. The overall proportion of non-contact to total ACL injuries was 55% (95% CI 48–62, I² = 82%; females: 63%, 95% CI 53–71, I² = 84%; males: 50%, 95% CI 42–58, I² = 86%). The overall incidence of non-contact ACL injuries was 0.07 per 1000 player-hours (95% CI 0.05–0.10, I² = 77%), and 0.05 per 1000 player-exposures (95% CI 0.03–0.07, I² = 97%). Injury incidence was higher in female athletes (0.14 per 1000 player-hours, 95% CI 0.10–0.19, I² = 40%) than male athletes (0.05 per 1000 player-hours, 95% CI 0.03–0.07, I² = 48%), and this difference was significant. Injury incidence during competition was higher (0.48 per 1000 player-hours, 95% CI 0.32–0.72, I² = 77%; 0.32 per 1000 player-exposures, 95% CI 0.15–0.70, I² = 96%) than during training (0.04 per 1000 player-hours, 95% CI 0.02–0.07, I² = 63%; 0.02 per 1000 player-exposures, 95% CI 0.01–0.05, I² = 86%) and these differences were significant. Heterogeneity across studies was generally high.

Conclusion

This study quantifies several key epidemiological findings for ACL injuries in team ball-sports. Non-contact ACL injuries represented over half of all ACL injuries sustained. The proportion of non-contact to total ACL injuries and injury incidence were higher in female than in male athletes. Injuries mostly occurred in competition settings.

中文翻译：

团体球类运动中非接触式前十字韧带损伤流行病学：按性别、年龄、运动项目、参与水平和暴露类型进行荟萃分析的系统评价

背景

并非所有前十字韧带 (ACL) 损伤都是可以预防的。虽然有些 ACL 损伤是不可避免的，例如因铲球造成的损伤，但其他发生在非接触情况下的损伤，例如在没有外部接触的情况下扭转和转动，可能更容易预防。由于 ACL 损伤通常发生在涉及跳跃、落地和切入动作的团体球类运动中，因此需要有关这些运动中非接触性 ACL 损伤的流行病学的准确信息，以量化其程度和负担，以指导降低风险工作的资源分配。

客观的

综合关于团体球类运动中非接触性损伤占总 ACL 损伤的发生率和比例的证据，按性别、年龄、运动项目、参与程度和暴露类型分类。

方法

从成立到 2021 年 7 月，对六个数据库（MEDLINE、EMBASE、Web of Science、CINAHL、Scopus 和 SPORTDiscus）进行了检索。其中包括团队球类运动的队列研究，报告膝关节损伤数量与暴露和损伤机制的关系。

结果

涵盖 13 项团体球类运动的 45 项研究被纳入其中。非接触性 ACL 损伤占总 ACL 损伤的总体比例为 55%（95% CI 48–62， I ² = 82%；女性：63%，95% CI 53–71， I ² = 84%；男性：50% ，95% CI 42–58， I ² = 86%）。非接触性 ACL 损伤的总体发生率为每 1000 名球员小时 0.07 例（95% CI 0.05–0.10， I ² = 77%），每 1000 名球员暴露时间 0.05 例（95% CI 0.03–0.07， I ² = 97） %）。女性运动员的损伤发生率（每 1000 小时 0.14 次，95% CI 0.10–0.19， I ² = 40%）高于男性运动员（每 1000 小时 0.05 次，95% CI 0.03–0.07， I ² = 48） %)，而且这种差异是显着的。比赛期间的受伤发生率比训练期间更高（每 1000 名球员小时 0.48，95% CI 0.32–0.72， I ² = 77%；每 1000 名球员暴露 0.32，95% CI 0.15–0.70， I ² = 96%）（每 1000 名玩家小时 0.04，95% CI 0.02–0.07， I ² = 63%；每 1000 名玩家暴露 0.02，95% CI 0.01–0.05， I ² = 86%），这些差异非常显着。研究之间的异质性普遍较高。