European geriatric medicine · 2025
Gait speed as a superior screening indicator for mild cognitive impairment compared to walk ratio and dual-task cost: a cross-sectional study.
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Wang Xiaoqin, Wu Jiani, Tian Qi, Liu Xintong, Yu Weihua, Lü Yang
Аннотация
BACKGROUND: The accurate and sensitive quantitative indicator for screening patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI) has not yet been established.
METHODS: Our study involved the measurement and comparison of clinical features and gait indicators among 96 patients with MCI, 66 patients with SCD, and 50 individuals with normal cognition (NC). Receiver operating characteristic (ROC) curve, multiple logistic regression, correlation clustering heatmap plot, and random forest modeling were used to evaluate the ability of gait indicators to differentiate disease.
RESULTS: No significant differences were observed in gait parameters between control and SCD groups [dual-task cost (DTC): p = 0.579; single-task gait speed: p = 0.656; dual gait speed: p = 0.951; single-task walk ratio: p = 0.683; dual-task walk ratio: p = 0.657]. Principal component analysis (PCA) revealed no distinct clustering patterns between these groups. For MCI discrimination, gait speed showed moderate predictive value (control vs. MCI: single-task AUC = 0.725, dual-task AUC = 0.726; SCD vs. MCI: single-task AUC = 0.733, dual-task AUC = 0.750). Both single-task (r = 0.36) and dual-task (r = 0.37) speeds correlated positively with MMSE scores. Multiple logistic regression identified single speed as a significant predictor of MCI (single-task: OR = 1.047; dual-task: OR = 1.05). Random forest analysis confirmed the importance of dual-task speed (mean decrease accuracy = 24.99).
CONCLUSION: This study identifies gait speed as superior to walk ratio and DTC for MCI detection, supporting its clinical adoption as a frontline screening tool.
METHODS: Our study involved the measurement and comparison of clinical features and gait indicators among 96 patients with MCI, 66 patients with SCD, and 50 individuals with normal cognition (NC). Receiver operating characteristic (ROC) curve, multiple logistic regression, correlation clustering heatmap plot, and random forest modeling were used to evaluate the ability of gait indicators to differentiate disease.
RESULTS: No significant differences were observed in gait parameters between control and SCD groups [dual-task cost (DTC): p = 0.579; single-task gait speed: p = 0.656; dual gait speed: p = 0.951; single-task walk ratio: p = 0.683; dual-task walk ratio: p = 0.657]. Principal component analysis (PCA) revealed no distinct clustering patterns between these groups. For MCI discrimination, gait speed showed moderate predictive value (control vs. MCI: single-task AUC = 0.725, dual-task AUC = 0.726; SCD vs. MCI: single-task AUC = 0.733, dual-task AUC = 0.750). Both single-task (r = 0.36) and dual-task (r = 0.37) speeds correlated positively with MMSE scores. Multiple logistic regression identified single speed as a significant predictor of MCI (single-task: OR = 1.047; dual-task: OR = 1.05). Random forest analysis confirmed the importance of dual-task speed (mean decrease accuracy = 24.99).
CONCLUSION: This study identifies gait speed as superior to walk ratio and DTC for MCI detection, supporting its clinical adoption as a frontline screening tool.