Parkinsonism & related disorders · 2026
Cognitive and motor dual task costs reveal distinct gait impairment phenotypes in Parkinson's disease.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Wang Yu, Wang Suyue, Mei Jianing, Zhou Yang, Tang Yunzhe, Wei Zijun, Tao Qingliang, Han Xueyi, Hu Jiyuan, Shi Yuhu, Zhang Yunyun
Аннотация
BACKGROUND: The clinical phenotypes and determinants of heterogeneous dual task gait impairment in Parkinson's disease (PD) remain unclear. We aimed to identify subtypes of dual task gait impairment in PD by comparing cognitive and motor dual task costs (DTC) and to elucidate their independent clinical correlates.
METHODS: This multicenter, cross-sectional study enrolled 268 PD patients. Participants underwent comprehensive clinical assessments and dual task Timed Up and Go (TUG) tests in the "OFF" state. K-means clustering was used to classify patients based on cognitive and motor DTC. Multiple linear regression models identified clinical predictors.
RESULTS: We identified three subtypes: "Dual Task Resilient" (n = 136), "Motor DTC Dominant" (MDD) (n = 84), and "Cognitive DTC Dominant" (CDD) (n = 48). A clinical dissociation was evident: the MDD subtype had worse motor function and mood, while the CDD subtype had poorer executive and global cognition. Regression confirmed that the Postural Instability and Gait Disorder (PIGD) score was the strongest predictor of motor DTC (β = 0.09, p = 0.002). Poorer Montreal Cognitive Assessment (MoCA) (β = -0.08, p = 0.002) and Frontal Assessment Battery (FAB) (β = -0.08, p = 0.038) scores were the strongest predictors of cognitive DTC.
CONCLUSIONS: PD patients exhibit three distinct, data-driven phenotypes of dual-task gait impairment based on cognitive and motor DTC. This novel framework clarifies the heterogeneity of this common deficit and offers new targets for individualized rehabilitation.
METHODS: This multicenter, cross-sectional study enrolled 268 PD patients. Participants underwent comprehensive clinical assessments and dual task Timed Up and Go (TUG) tests in the "OFF" state. K-means clustering was used to classify patients based on cognitive and motor DTC. Multiple linear regression models identified clinical predictors.
RESULTS: We identified three subtypes: "Dual Task Resilient" (n = 136), "Motor DTC Dominant" (MDD) (n = 84), and "Cognitive DTC Dominant" (CDD) (n = 48). A clinical dissociation was evident: the MDD subtype had worse motor function and mood, while the CDD subtype had poorer executive and global cognition. Regression confirmed that the Postural Instability and Gait Disorder (PIGD) score was the strongest predictor of motor DTC (β = 0.09, p = 0.002). Poorer Montreal Cognitive Assessment (MoCA) (β = -0.08, p = 0.002) and Frontal Assessment Battery (FAB) (β = -0.08, p = 0.038) scores were the strongest predictors of cognitive DTC.
CONCLUSIONS: PD patients exhibit three distinct, data-driven phenotypes of dual-task gait impairment based on cognitive and motor DTC. This novel framework clarifies the heterogeneity of this common deficit and offers new targets for individualized rehabilitation.