Diagnostic accuracy of multi-component spatial-temporal gait parameters in older adults with amnestic mild cognitive impairment - Huang, Shuyun; Hou, Xiaobing; Liu, Yajing; Shang, Pan; Luo, Jiali; Lv, Zeping; Zhang, Weiping; Lin, Biqing; Huang, Qiulan; Tao, Shuai; Wang, Yukai; Zhang, Chengguo; et al. (Frontiers in Human Neuroscience, 2022)
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.