Background:

Hamstring strain injuries are the most common injuries in team sports. Biceps femoris long head architecture is associated with the risk of hamstring injury in soccer. To assess the overall predictive ability of architectural variables, risk factors need to be applied to and validated across different cohorts.

Purpose:

To assess the generalizability of previously established risk factors for a hamstring strain injury (HSI), including demographics, injury history, and biceps femoris long head (BFlh) architecture to predict HSIs in a cohort of elite Australian football players.

Study Design:

Cohort study; Level of evidence, 3.

Methods:

Demographic, injury history, and BFlh architectural data were collected from elite soccer (n = 152) and Australian football (n = 169) players at the beginning of the preseason for their respective competitions. Any prospectively occurring HSIs were reported to the research team. Optimal cut points for continuous variables used to determine an association with the HSI risk were established from previously published data in soccer and subsequently applied to the Australian football cohort to derive the relative risk (RR) for these variables. Logistic regression models were built using data from the soccer cohort and utilized to estimate the probability of an injury in the Australian football cohort. The area under the curve (AUC) and Brier score were the primary outcome measures to assess the performance of the logistic regression models.

Results:

A total of 27 and 30 prospective HSIs occurred in the soccer and Australian football cohorts, respectively. When using cut points derived from the soccer cohort and applying these to the Australian football cohort, only older athletes (aged ≥25.4 years; RR, 2.7 [95% CI, 1.4-5.2]) and those with a prior HSI (RR, 2.5 [95% CI, 1.3-4.8]) were at an increased risk of HSIs. Using the same approach, height, weight, fascicle length, muscle thickness, pennation angle, and relative fascicle length were not significantly associated with an increased risk of HSIs in Australian football players. The logistic regression model constructed using age and prior HSIs performed the best (AUC = 0.67; Brier score = 0.14), with the worst performing model being the one that was constructed using pennation angle (AUC = 0.53; Brier score = 0.18).

Conclusion:

Applying cut points derived from previously published data in soccer to a dataset from Australian football identified older age and prior HSIs, but none of the modifiable HSI risk factors, to be associated with an injury. The transference of HSI risk factor data between soccer and Australian football appears limited and suggests that cohort-specific cut points must be established.

中文翻译：

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使用源自足球的股二头肌结构风险因素预测澳大利亚足球中的腿筋损伤

背景：

腿筋拉伤是团队运动中最常见的损伤。股二头肌长头结构与足球比赛中腿筋受伤的风险有关。为了评估架构变量的整体预测能力，需要将风险因素应用于不同的队列并进行验证。

目的：

评估先前确定的腿筋拉伤 (HSI) 风险因素的普遍性，包括人口统计学、受伤史和股二头肌长头 (BFlh) 结构，以预测一组精英澳大利亚足球运动员的 HSI。

学习规划：

队列研究；证据等级，3。

方法：

人口统计学、伤病史和 BFlh 建筑数据是在各自比赛的季前赛开始时从精英足球 (n = 152) 和澳大利亚足球 (n = 169) 球员那里收集的。任何预期发生的 HSI 都会报告给研究团队。用于确定与 HSI 风险关联的连续变量的最佳切点是根据先前公布的足球数据建立的，随后应用于澳大利亚足球队列以推导这些变量的相对风险 (RR)。Logistic 回归模型是使用来自足球队的数据建立的，并用于估计澳大利亚足球队受伤的可能性。曲线下面积 (AUC) 和 Brier 评分是评估逻辑回归模型性能的主要结果指标。

结果：

英式足球和澳式橄榄球队列中分别发生了 27 例和 30 例预期 HSI。当使用来自足球队列的切点并将其应用于澳大利亚足球队列时，只有年龄较大的运动员（年龄≥25.4 岁；RR，2.7 [95% CI，1.4-5.2]）和之前有 HSI 的运动员（RR，2.5 [95% CI, 1.3-4.8]) 患 HSI 的风险增加。使用相同的方法，身高、体重、分束长度、肌肉厚度、羽状角和相对分束长度与澳大利亚足球运动员 HSI 风险增加没有显着相关性。使用年龄和先验 HSI 构建的逻辑回归模型表现最好（AUC = 0.67；Brier 评分 = 0.14），表现最差的模型是使用羽状角构建的模型（AUC = 0.53；Brier 评分 = 0.18）。

结论：

将源自先前发布的足球数据的切点应用于澳大利亚足球的数据集，确定了年龄较大和先前的 HSI，但没有任何可修改的 HSI 风险因素与受伤相关。HSI 风险因素数据在英式足球和澳式橄榄球之间的转移似乎有限，表明必须建立特定队列的切点。