Diagnostic accuracy of multi-component spatial-temporal gait parameters in older adults with amnestic mild cognitive impairment

Shuyun Huang; Xiaobing Hou; Yajing Liu; Pan Shang; Jiali Luo; Zeping Lv; Weiping Zhang; Biqing Lin; Qiulan Huang; Shuai Tao; Yukai Wang; Chengguo Zhang; Lushi Chen; Suyue Pan; Haiqun Xie

doi:10.3389/fnhum.2022.911607

Diagnostic accuracy of multi-component spatial-temporal gait parameters in older adults with amnestic mild cognitive impairment

Front Hum Neurosci. 2022 Sep 15:16:911607. doi: 10.3389/fnhum.2022.911607. eCollection 2022.

Authors

Shuyun Huang^{1

2}, Xiaobing Hou¹, Yajing Liu¹, Pan Shang¹, Jiali Luo¹, Zeping Lv³, Weiping Zhang¹, Biqing Lin¹, Qiulan Huang¹, Shuai Tao⁴, Yukai Wang¹, Chengguo Zhang¹, Lushi Chen¹, Suyue Pan², Haiqun Xie¹

Affiliations

¹ Department of Neurology, First People's Hospital of Foshan, Foshan, Guangdong, China.
² Department of Neurology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
³ National Research Center for Rehabilitation Technical Aids, Rehabilitation Hospital, Beijing, China.
⁴ Dalian Key Laboratory of Smart Medical and Health, Dalian University, Dalian, China.

Abstract

Objective: This study aimed to develop a diagnostic model of multi-kinematic parameters for patients with amnestic mild cognitive impairment (aMCI).

Method: In this cross-sectional study, 94 older adults were included (33 cognitively normal, CN; and 61 aMCI). We conducted neuropsychological battery tests, such as global cognition and cognitive domains, and collected gait parameters by an inertial-sensor gait analysis system. Multivariable regression models were used to identify the potential diagnostic variables for aMCI. Receiver operating characteristic (ROC) curves were applied to assess the diagnostic accuracy of kinematic parameters in discriminating aMCI from healthy subjects.

Results: Multivariable regression showed that multi-kinematic parameters were the potential diagnostic variables for aMCI. The multi-kinematic parameter model, developed using Timed Up and Go (TUG) time, stride length, toe-off/heel stride angles, one-leg standing (OLS) time, and braking force, showed areas under ROC (AUC), 0.96 [95% confidence interval (CI), 0.905-0.857]; sensitivity, 0.90; and specificity, 0.91. In contrast, a single kinematic parameter's sensitivity was 0.26-0.95 and specificity was 0.21-0.90. Notably, the separating capacity of multi-kinematic parameters was highly similar to Montreal Cognitive Assessment (MoCA; AUC: 0.96 vs. 0.95). Compared to cognitive domain tests, the separating ability was comparable to Auditory Verbal Learning Test (AVLT) and Boston Naming Test (BNT; AUC: 0.96 vs. 0.97; AUC: 0.96 vs. 0.94).

Conclusion: We developed one diagnostic model of multi-kinematic parameters for patients with aMCI in Foshan.

Keywords: amnestic mild cognitive impairment; diagnostic accuracy; inertial-sensor gait analysis system; multi-kinematic parameters; receiver operating characteristic.