Bruce Scott L, Wilkerson Gary B
Masters of Athletic Training Program, Arkansas State University, Jonesboro, AR, United States.
Department of Health and Human Performance, University of Tennessee at Chattanooga, Chattanooga, TN, United States.
Front Sports Act Living. 2021 Oct 20;3:733567. doi: 10.3389/fspor.2021.733567. eCollection 2021.
Clinical prediction models are useful in addressing several orthopedic conditions with various cohorts. American football provides a good population for attempting to predict injuries due to their relatively high injury rate. Physical performance can be assessed a variety of ways using an assortment of different tests to assess a diverse set of metrics, which may include reaction time, speed, acceleration, and deceleration. Asymmetry, the difference between right and left performance has been identified as a possible risk factor for injury. The purpose of this study was to determine the whole-body reactive agility metrics that would identify Division I football players who were at elevated risk for core, and lower extremity injuries (CLEI). This cohort study utilized 177 Division I football players with a total of 57 CLEI suffered who were baseline tested prior to the season. Single-task and dual-task whole-body reactive agility movements in lateral and diagonal direction reacting to virtual reality targets were analyzed separately. Receiver operator characteristic (ROC) analyses narrowed the 34 original predictor variables to five variables. Logistic regression analysis determined the three strongest predictors of CLEI for this cohort to be: lateral agility acceleration asymmetry, lateral flanker deceleration asymmetry, and diagonal agility reaction time average. Univariable analysis found odds ratios to range from 1.98 to 2.75 for these predictors of CLEI. ROC analysis had an area under the curve of 0.702 for any combination of two or more risk factors produced an odds ratio of 5.5 for risk of CLEI. These results suggest an asymmetry of 8-15% on two of the identified metrics or a slowed reaction time of ≥0.787 s places someone at increased risk of injury. Sixty-three percent (36/57) of the players who sustained an injury had ≥2 positive predictors In spite of the recognized limitation, these finding support the belief that whole-body reactive agility performance can identify Division I football players who are at elevated risk for CLEI.
临床预测模型对于解决不同队列中的多种骨科疾病很有用。美式橄榄球运动因其相对较高的受伤率，为尝试预测损伤提供了一个合适的人群。身体表现可以通过各种不同的测试，以多种方式进行评估，以测量一系列不同的指标，其中可能包括反应时间、速度、加速度和减速。不对称性，即左右表现之间的差异，已被确定为可能的损伤风险因素。本研究的目的是确定全身反应敏捷性指标，以识别一级橄榄球运动员中核心部位和下肢损伤（CLEI）风险较高的运动员。这项队列研究对177名一级橄榄球运动员进行了研究，这些运动员在赛季前进行了基线测试，共发生了57例CLEI损伤。分别分析了对虚拟现实目标做出反应的横向和对角方向的单任务和双任务全身反应敏捷性动作。受试者工作特征（ROC）分析将34个原始预测变量缩小到5个变量。逻辑回归分析确定该队列中CLEI的三个最强预测因素为：横向敏捷性加速度不对称、侧翼横向减速不对称和对角敏捷性反应时间平均值。单变量分析发现，这些CLEI预测因素的优势比在1.98至2.75之间。对于两个或更多风险因素的任何组合，ROC分析的曲线下面积为0.702，CLEI风险的优势比为5.5。这些结果表明，在两个已确定的指标上存在8-15%的不对称性，或反应时间减慢≥0.787秒，会使某人受伤风险增加。63%（36/57）的受伤球员有≥2个阳性预测因素。尽管存在公认的局限性，但这些发现支持这样一种观点，即全身反应敏捷性表现可以识别出CLEI风险较高的一级橄榄球运动员。
