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估计中风后受影响上肢Fugl-Meyer评估评分的潜在等级数量。

Estimating the Number of Latent Ranks of the Fugl-Meyer Assessment Score for the Affected Upper Extremity After Stroke.

作者信息

Hara Kensuke, Tauchi Yuta, Hanada Keisuke, Takebayashi Takashi

机构信息

Graduate School of Rehabilitation, Osaka Metropolitan University, Osaka, JPN.

Department of Rehabilitation Medicine, Hyogo Medical University Sasayama Medical Center, Tamba-Sasayama, JPN.

出版信息

Cureus. 2025 May 16;17(5):e84210. doi: 10.7759/cureus.84210. eCollection 2025 May.

Abstract

Many clinical stroke rehabilitation studies have adopted the upper extremity motor section of the Fugl-Meyer Assessment (FMA-UE). In addition, some clinical studies use specific FMA-UE scores as inclusion criteria. However, it remains unclear whether it is appropriate to determine the criterion based on the total score of FMA-UE. This study aimed to determine a highly valid criterion using the latent rank theory (LRT) that can estimate the number of latent ranks of FMA-UE. This was a multicenter cross-sectional study; patients with stroke were recruited from 25 hospitals between March 2018 and April 2022. For all patients, FMA-UE results and participant information were collected. The collected FMA-UE data were divided into proximal and distal items and verified the dimensionality of the data. After that, the LRT was used to determine the latent ranks. Seven ranks were considered the most appropriate for proximal and distal items when estimating the number of latent ranks. These results suggest that FMA-UE has high construct validity. Furthermore, we recommend the novel interpretability of FMA-UE, which previous studies have yet to find. Although this cross-sectional study cannot directly guide stroke patients' recovery processes, it may be practical for optimizing the difficulty of stroke rehabilitation.

摘要

许多临床中风康复研究都采用了Fugl-Meyer评估量表(FMA-UE)的上肢运动部分。此外,一些临床研究将特定的FMA-UE分数用作纳入标准。然而,基于FMA-UE的总分来确定标准是否合适仍不清楚。本研究旨在使用能够估计FMA-UE潜在等级数量的潜在等级理论(LRT)来确定一个高度有效的标准。这是一项多中心横断面研究;2018年3月至2022年4月期间,从25家医院招募了中风患者。收集了所有患者的FMA-UE结果和参与者信息。将收集到的FMA-UE数据分为近端和远端项目,并验证数据的维度。之后,使用LRT来确定潜在等级。在估计潜在等级数量时,七个等级被认为对近端和远端项目最为合适。这些结果表明FMA-UE具有较高的结构效度。此外,我们推荐FMA-UE具有新颖的可解释性,这是以往研究尚未发现的。虽然这项横断面研究不能直接指导中风患者的恢复过程,但它可能对优化中风康复的难度具有实际意义。

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