Department of Industrial and Operations Engineering, University of Michigan, 1205 Beal Ave, Ann Arbor, MI, 48109, USA.
School of Kinesiology, University of Michigan, Ann Arbor, MI, USA.
Sports Med. 2018 Jul;48(7):1739-1749. doi: 10.1007/s40279-018-0880-x.
Many concussion assessment methods exist, but few studies quantify the performance of these methods to determine which can best assess acute concussion alone or in combination.
The objectives of this study were to evaluate: (1) selected concussion assessments for acute concussion assessment; (2) the utility of change scores for acute concussion assessment; and (3) concussion assessment capabilities when constrained to limited clinical data or objective clinical measures.
The 'acute concussion' group contained assessments from < 6 h post-injury (n = 560) and 24-48 h post-injury (n = 733). The 'normal performance' group contained assessments from baseline testing (n = 842) and unrestricted return to play (n = 707) timepoints. Univariate and multivariate logistic regression models were created separately for < 6- and 24- to 48-h timepoints. Models were evaluated on sensitivity, specificity, and area under the receiver operating characteristic curve.
Within the univariate analysis, Sport Concussion Assessment Tool symptom assessments had the highest combination of sensitivity, specificity, and area under the receiver operating characteristic curve, with values up to 0.93, 0.97, and 0.98, respectively. Full models had a sensitivity, specificity, and area under the receiver operating characteristic curve up to 0.94, 0.97, and 0.99, respectively, and outperformed all univariate models, raw score models, and objective models. Objective models were outperformed by all multivariate models and the univariate models containing only Sport Concussion Assessment Tool symptom assessments.
Results support the use of multidimensional assessment batteries over single instruments and suggest the importance of self-reported symptoms in acute concussion assessment. Balance assessments, however, may not provide additional benefit when symptom and neurocognitive assessments are available. Additionally, change scores provide some clinical utility over raw scores, but the difference may not be clinically meaningful.
有许多 concussion 评估方法,但很少有研究量化这些方法的性能,以确定哪些方法可以单独或组合最佳评估急性 concussion。
本研究的目的是评估:(1)用于急性 concussion 评估的选定 concussion 评估;(2)急性 concussion 评估中变化分数的效用;以及(3)在受限的临床数据或客观临床测量约束下的 concussion 评估能力。
“急性 concussion”组包含伤后<6 小时(n=560)和 24-48 小时(n=733)的评估。“正常表现”组包含基线测试(n=842)和不受限制重返比赛(n=707)的评估。分别为<6 小时和 24-48 小时的时间点创建了单变量和多变量逻辑回归模型。模型的评估指标包括敏感性、特异性和接收者操作特征曲线下面积。
在单变量分析中,运动 concussion 评估工具症状评估具有最高的敏感性、特异性和接收者操作特征曲线下面积,其值分别高达 0.93、0.97 和 0.98。全模型的敏感性、特异性和接收者操作特征曲线下面积分别高达 0.94、0.97 和 0.99,并且优于所有单变量模型、原始分数模型和客观模型。客观模型优于所有多变量模型和仅包含运动 concussion 评估工具症状评估的单变量模型。
结果支持使用多维评估工具而不是单一工具,并且表明自我报告的症状在急性 concussion 评估中的重要性。然而,当有症状和神经认知评估时,平衡评估可能不会提供额外的益处。此外,与原始分数相比,变化分数提供了一些临床效用,但差异可能没有临床意义。