Bonnette Scott, Diekfuss Jed A, Grooms Dustin, Myer Gregory D, Meehan William P, Howell David R
The SPORT Center, Division of Sports Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
The SPORT Center, Division of Sports Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Neurosci Lett. 2020 Jun 11;729:134975. doi: 10.1016/j.neulet.2020.134975. Epub 2020 Apr 13.
Postural sway is significantly affected by a mild traumatic brain injury, or concussion, and myriad methods have been developed to quantify the severity of concussion symptoms. The current manuscript quantifies postural sway-as measured by an inertial sensor-in youth athletes with concussion (n = 43, age = 14.4 ± 2.3 years, 56% female, tested median 7 days post-concussion) and healthy controls (n = 38, age = 14.9 ± 2.0 years, 55% female) during single-task and dual-task postural sway. A nonlinear analysis (i.e., recurrence quantification analysis [RQA]) and several common linear measures were used to quantify postural sway. Respectively, the two complementary types of analyses describe the structure and magnitude of postural sway. We hypothesized that participants who recently experienced a concussion would display differing postural sway dynamics (i.e., different in structure and magnitude) than control participants who had not experienced a concussion. Additionally, a logistic regression was performed to determine which combination of variables (nonlinear and linear) and task (single and dual) would best differentiate concussion and control participants. Significant differences between concussion and control participants were found in percent determinism, laminarity, and standard deviation of postural sway acceleration in both the single and the dual task. In the single task alone, mean diagonal line length and trapping time were additionally significantly different between groups. Moreover, the logistic regression model revealed that a mixture of linear and nonlinear measures across both single and dual tasks best classified concussed and non-concussed participants. Additionally, history of concussion was found to be a significant covariate in the model. These results extend past observations by demonstrating that a combination of posture sway tasks and measurements best differentiate participants with a concussion. These results highlight the need for future studies to replicate the findings in different populations and further determine which combinations of postural sway tasks and measurements best classify participants with concussions.
轻度创伤性脑损伤（即脑震荡）会显著影响姿势摆动，人们已开发出多种方法来量化脑震荡症状的严重程度。本研究通过惯性传感器测量青少年脑震荡运动员（n = 43，年龄 = 14.4 ± 2.3岁，56%为女性，脑震荡后中位测试时间为7天）和健康对照组（n = 38，年龄 = 14.9 ± 2.0岁，55%为女性）在单任务和双任务姿势摆动过程中的姿势摆动情况。采用非线性分析（即递归量化分析[RQA]）和几种常见的线性测量方法来量化姿势摆动。这两种互补类型的分析分别描述了姿势摆动的结构和幅度。我们假设，近期经历过脑震荡的参与者与未经历过脑震荡的对照参与者相比，会表现出不同的姿势摆动动态（即结构和幅度不同）。此外，进行了逻辑回归分析，以确定哪些变量（非线性和线性）和任务（单任务和双任务）的组合能最佳区分脑震荡参与者和对照参与者。在单任务和双任务中，脑震荡参与者和对照参与者在确定性百分比、层流性和姿势摆动加速度标准差方面均存在显著差异。仅在单任务中，组间平均对角线长度和捕获时间也存在显著差异。此外，逻辑回归模型显示，单任务和双任务中线性和非线性测量的混合能最佳区分脑震荡参与者和未脑震荡参与者。此外，发现脑震荡史是该模型中的一个显著协变量。这些结果通过证明姿势摆动任务和测量的组合能最佳区分脑震荡参与者，扩展了以往的观察结果。这些结果凸显了未来研究在不同人群中重复这些发现并进一步确定哪些姿势摆动任务和测量组合能最佳区分脑震荡参与者的必要性。
