Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Novartis Pharma AG, Basel, Switzerland.
Arch Phys Med Rehabil. 2020 Feb;101(2):234-241. doi: 10.1016/j.apmr.2019.07.016. Epub 2019 Aug 30.
To examine the feasibility, reliability, granularity, and convergent validity of a video-based pairwise comparison technique that uses algorithmic support to enable automated rating of motor dysfunction in patients with multiple sclerosis (MS).
Feasibility and larger cross-sectional cohort study.
The outpatient clinic of 2 specialist university medical centers.
Selected sample from a cohort of patients with MS participating in the Assess MS study (N=42). Videos were randomly drawn from each strata of the ataxia severity-degrees as defined in the Expanded Disability Status Scale (EDSS). In Basel: 19 videos of 17 patients (mean age, 43.4±11.6y; 10 women). In Amsterdam: 50 videos of 25 patients (mean age, 50.0±10.0y; 15 women).
Not applicable.
In each center, neurologists (n=13; n=10) viewed pairs of videos of patients performing standardized movements (eg, finger-to-nose test) to assess relative performance. A comparative assessment score was calculated for each video using the TrueSkill algorithm and analyzed for intrarater (test-retest; ratio of agreement) and interrater reliability (intraclass correlation coefficient [ICC] for absolute agreement) and convergent validity (Spearman ρ). Granularity was estimated from the average difference in comparative assessment scores at which 80% of neurologists considered performance to be different.
Intrarater reliability was excellent (median ratio of agreement≥0.87). The comparative assessment scores calculated from individual neurologists demonstrated good-excellent ICCs for interrater reliability (0.89; 0.71). The comparative assessment scores correlated (very) highly with their Neurostatus-EDSS equivalent (ρ=0.78, P<.001; ρ=0.91, P<.05), suggesting a more fine-grained rating.
Video-based pairwise comparison of motor dysfunction allows for reliable and fine-grained capturing of clinical judgment about neurologic performance, which can contribute to the development of a consistent quantified metric of motor ability in MS.
研究一种基于视频的配对比较技术的可行性、可靠性、粒度和收敛效度,该技术使用算法支持实现对多发性硬化症(MS)患者运动功能障碍的自动评分。
可行性和更大的横断面队列研究。
2 家专科大学医学中心的门诊。
参与 Assess MS 研究的 MS 队列患者的选择样本(N=42)。视频是根据扩展残疾状况量表(EDSS)定义的共济失调严重程度等级随机抽取的。在巴塞尔:17 名患者的 19 个视频(平均年龄,43.4±11.6 岁;10 名女性)。在阿姆斯特丹:25 名患者的 50 个视频(平均年龄,50.0±10.0 岁;15 名女性)。
不适用。
在每个中心,神经科医生(n=13;n=10)观看患者进行标准化运动(例如,指鼻试验)的视频对,以评估相对表现。使用 TrueSkill 算法为每个视频计算比较评估分数,并分析内部评估(测试-再测试;一致性比)和内部评估可靠性(绝对一致性的组内相关系数 [ICC])和收敛效度(Spearman ρ)。粒度是从 80%的神经科医生认为表现不同的比较评估分数的平均差异估计的。
内部评估可靠性非常好(中位数一致性比≥0.87)。从个别神经科医生计算的比较评估分数显示出非常好的内部评估可靠性的 ICC(0.89;0.71)。比较评估分数与他们的 Neurostatus-EDSS 等效物高度相关(ρ=0.78,P<.001;ρ=0.91,P<.05),表明评分更精细。
运动功能障碍的基于视频的配对比较允许可靠且精细地捕捉对神经表现的临床判断,这有助于开发 MS 中运动能力的一致量化指标。