Goris Maaike, Ginis Pieter, Hansen Clint, Schlenstedt Christian, Hausdorff Jeffrey M, D'Cruz Nicholas, Vandenberghe Wim, Maetzler Walter, Nieuwboer Alice, Gilat Moran
Department of Rehabilitation Sciences, Neurorehabilitation Research Group (eNRGy), KU Leuven, Leuven, Belgium.
Department of Neurology, University Hospital Schleswig-Holstein, Christian-Albrechts-University Kiel, Kiel, Germany.
Front Neurol. 2025 Jan 8;15:1508800. doi: 10.3389/fneur.2024.1508800. eCollection 2024.
Freezing of gait (FOG) is a disabling symptom for people with Parkinson's disease (PwPD). Turning on the spot for one minute in alternating directions (360 turn) while performing a cognitive dual-task (DT) is a fast and sensitive way to provoke FOG. The FOG-index is a widely used wearable sensor-based algorithm to quantify FOG severity during turning. Despite that, the FOG-index's classification performance and criterion validity is not tested against the gold standard (i.e., video-rated time spent freezing). Therefore, this study aimed to evaluate the FOG-index's classification performance and criterion validity to assess FOG severity during 360 turn. Additionally, we investigated the FOG-index's optimal cutoff values to differentiate between PwPD with and without FOG.
164 PwPD self-reported the presence of FOG on the New Freezing of Gait Questionnaire (NFOGQ) and performed the DT 360 turn in the ON medication state while being videoed and wearing five wearable sensors. Two independent clinical experts rated FOG on video. ROC-AUC values assessed the FOG-index's classification accuracy against self-reported FOG and expert ratings. Spearman-rho was used to evaluate the correlation between expert and FOG-index ratings of FOG severity.
Twenty-eight patients self-reported FOG, while 104 were classified as a freezer by the experts. The FOG-index had limited classification agreement with the NFOGQ (AUC = 0.60, = 0.115, sensitivity 46.4%, specificity 72.8%) and the experts (AUC = 0.65, < 0.001, sensitivity 68.3%, specificity 61.7%). Only weak correlations were found between the algorithm outputs and expert ratings for FOG severity (rho = 0.13-0.38).
A surprisingly large discrepancy was found between self-reported and expert-rated FOG during the 360 turning task, indicating PwPD do not always notice FOG in daily life. The FOG-index achieved suboptimal classification performance and poor criterion validity to assess FOG severity. Regardless, 360 turning proved a sensitive task to elicit FOG. Further development of the FOG-index is warranted, and long-term follow-up studies are needed to assess the predictive value of the 360 turning task for classifying FOG conversion.
冻结步态（FOG）是帕金森病患者（PwPD）的一种致残症状。在执行认知双重任务（DT）时，以交替方向原地转身一分钟（360度转身）是诱发FOG的一种快速且敏感的方法。FOG指数是一种广泛使用的基于可穿戴传感器的算法，用于量化转身过程中FOG的严重程度。尽管如此，FOG指数的分类性能和标准效度尚未与金标准（即视频评定的冻结时间）进行对比测试。因此，本研究旨在评估FOG指数在360度转身过程中评估FOG严重程度的分类性能和标准效度。此外，我们还研究了FOG指数的最佳临界值，以区分有无FOG的PwPD。
164名PwPD在新版冻结步态问卷（NFOGQ）上自我报告了FOG的存在，并在服药状态下进行DT 360度转身，同时进行录像并佩戴五个可穿戴传感器。两名独立的临床专家对录像中的FOG进行评分。ROC-AUC值评估了FOG指数相对于自我报告的FOG和专家评分的分类准确性。Spearman-rho用于评估专家评分与FOG指数对FOG严重程度评分之间的相关性。
28名患者自我报告有FOG，而专家将104名患者分类为冻结者。FOG指数与NFOGQ（AUC = 0.60， = 0.115，敏感性46.4%，特异性72.8%）和专家（AUC = 0.65， < 0.001，敏感性68.3%，特异性61.7%）的分类一致性有限。算法输出与专家对FOG严重程度的评分之间仅发现弱相关性（rho = 0.13 - 0.38）。
在360度转身任务中，自我报告的FOG与专家评定的FOG之间存在惊人的巨大差异，这表明PwPD在日常生活中并不总是能察觉到FOG。FOG指数在评估FOG严重程度方面达到了次优的分类性能和较差的标准效度。尽管如此，360度转身被证明是诱发FOG的一项敏感任务。FOG指数有必要进一步开发，并且需要进行长期随访研究，以评估360度转身任务对分类FOG转换的预测价值。
