Evidence map›Paper›PMID 42152795›Full record

ArticleBrain and behavior2026

Quantitative Gait Analysis Reveals Distinct Patterns Associated With Pyramidal Involvement in Amyotrophic Lateral Sclerosis: A Cross-Sectional Study.

Nan Hu, Ming Qi, Ning Su, Dingding Zhang, Jiangxia Zhang, Yun Xu, Kai Wang, Yuming Xu, Zhenzhong Li, Bo Hu and 13 more

Abstract read
In one paragraph

Article in Brain and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

23 authors.

Nan HuDepartment of Neurology, Peking Union Medical College Hospital, Beijing, China.
Ming QiDepartment of Neurology, Peking Union Medical College Hospital, Beijing, China.
Ning SuDepartment of Neurology, Peking Union Medical College Hospital, Beijing, China.
Dingding ZhangDepartment of Neurology, Peking Union Medical College Hospital, Beijing, China.
Jiangxia ZhangDepartment of Neurology, Peking Union Medical College Hospital, Beijing, China.
Yun XuDepartment of Neurology, Nanjing Drum Tower Hospital, Nanjing, China.
Kai WangDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Yuming XuDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Zhenzhong LiDepartment of Neurology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Bo HuDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lihua WangDepartment of Neurology, the Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Bo WuDepartment of Neurology, West China Hospital of Sichuan University, Chengdu, China.
Lan ChuDepartment of Neurology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Yinzhou WangDepartment of Neurology, Fujian Province Hospital, Fuzhou, China.
Hong JiangDepartment of Neurology, Xiangya Hospital of Central South University, Changsha, China.
Zhengqi LuDepartment of Neurology, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Jian WuDepartment of Neurology, Beijing Tsinghua Changgung Hospital affiliated to Tsinghua University, Beijing, China.
Xiangmin FanInstitute of Software, Chinese Academy of Sciences, Beijing, China.
Fei HanDepartment of Neurology, Peking Union Medical College Hospital, Beijing, China.
Feng TianInstitute of Software, Chinese Academy of Sciences, Beijing, China.
Jing YuanDepartment of Neurology, Peking Union Medical College Hospital, Beijing, China.
Mingsheng LiuDepartment of Neurology, Peking Union Medical College Hospital, Beijing, China.
Yicheng ZhuDepartment of Neurology, Peking Union Medical College Hospital, Beijing, China.

Funding

CAMS Innovation Fund for Medical Sciences CIFMS 2021-I2M-1-003Ministry of Industry and Information Technology of ChinaNational Science and Technology Major Project
6 · The paper itself

Abstract

objectiveTo dissect specific gait abnormalities associated with upper motor neuron (UMN) dysfunction in amyotrophic lateral sclerosis (ALS) by controlling for overall disease severity and to develop a multivariate classification model.

methodsWe performed 3D gait analysis on 118 ALS patients and 1796 healthy controls (HC). ALS patients were categorized into those with ALS with UMN dysfunction((ALS-UMN), n = 70) and those without ALS without UMN signs ((ALS-Numn), n = 48) lower limb UMN signs based on neurological examination. Gait parameters were compared, and their association with UMN involvement was analyzed using partial correlation (controlling for ALSFRS-R score) and machine learning models (Random Forest and Least Absolute Shrinkage and Selection Operator (Lasso) regression).

resultsCompared with HC, ALS patients exhibited widespread gait deterioration (e.g., reduced speed, increased step width, p < 0.001). After controlling for ALSFRS-R, specific parameters, including reduced stride, increased step width, prolonged double support, and elevated gait cycle time asymmetry, remained independently associated with UMN severity (PENN score, p < 0.01). A multivariate model incorporating key features demonstrated fair discriminative ability for identifying ALS-UMN patients, with an area under the curve (AUC) of 0.690, a sensitivity of 0.816, and a specificity of 0.418.

conclusionQuantitative gait analysis reveals a distinct spatiotemporal pattern linked to UMN dysfunction in ALS. A model based on gait features shows potential, particularly high sensitivity, for identifying patients with pyramidal signs, supporting the exploratory utility of objective gait metrics for motor phenotyping in ALS, pending external validation.

Indexed as

Amyotrophic Lateral SclerosisGait AnalysisGait Disorders, NeurologicAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedMotor NeuronsSeverity of Illness Indexamyotrophic lateral sclerosisgaitUMN dysfunction

Identifiers

PMID42152795
PMCPMC13184536

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.