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 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; 61 aMCI). We conducted neuropsychological battery tests, including global cognition and cognitive domains, 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 parameters model developed using TUG time, stride length, toe-off/heel stride angles, one-leg standing 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, 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 domains 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). Conclusions: We developed one diagnostic model of multi-kinematic parameters for patients with aMCI in Foshan.