Differential cognitive functioning in the digital clock drawing test in AD-MCI and PD-MCI populations

被引:1
作者
Wang, Chen [1 ]
Li, Kai [2 ,3 ]
Huang, Shouqiang [1 ]
Liu, Jiakang [1 ]
Li, Shuwu [1 ]
Tu, Yuting [1 ]
Wang, Bo [1 ]
Zhang, Pengpeng [1 ]
Luo, Yuntian [2 ]
Chen, Tong [4 ,5 ]
机构
[1] Zhejiang Chinese Med Univ, Sch Med Technol & Informat Engn, Hangzhou, Peoples R China
[2] Hangzhou Med Coll, Sch Informat Engn, Hangzhou, Peoples R China
[3] Hangzhou Med Coll, Zhejiang Engn Res Ctr Brain Cognit & Brain Dis Dig, Hangzhou, Peoples R China
[4] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 2, Dept Neurol, Beijing, Peoples R China
[5] Chinese Peoples Liberat Army Gen Hosp, Natl Clin Res Ctr Geriatr Dis, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Alzheimer's disease; Parkinson's disease; mild cognitive impairment; digital clock drawing test; cognitive function; digital biomarkers; PARKINSONS-DISEASE; IMPAIRMENT; ALZHEIMERS; DEMENTIA; DEFICITS;
D O I
10.3389/fnins.2025.1558448
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Background: Mild cognitive impairment (MCI) is common in Alzheimer's disease (AD) and Parkinson's disease (PD), but there are differences in pathogenesis and cognitive performance between Mild cognitive impairment due to Alzheimer's disease (AD-MCI) and Parkinson's disease with Mild cognitive impairment (PD-MCI) populations. Studies have shown that assessments based on the digital clock drawing test (dCDT) can effectively reflect cognitive deficits. Based on this, we proposed the following research hypothesis: there is a difference in cognitive functioning between AD-MCI and PD-MCI populations in the CDT, and the two populations can be effectively distinguished based on this feature. Methods: To test this hypothesis, we designed the dCDT to extract digital biomarkers that can characterize and quantify cognitive function differences between AD-MCI and PD-MCI populations. We enrolled a total of 40 AD-MCI patients, 40 PD-MCI patients, 41 PD with normal cognition (PD-NC) patients and 40 normal cognition (NC) controls. Results: Through a cross-sectional study, we revealed a difference in cognitive function between AD-MCI and PD-MCI populations in the dCDT, which distinguished AD-MCI from PD-MCI patients, the area under the roc curve (AUC) = 0.923, 95% confidence interval (CI) = 0.866-0.983. The AUC for effective differentiation between AD-MCI and PD-MCI patients with high education (>= 12 years of education) was 0.968, CI = 0.927-1.000. By correlation analysis, we found that the overall plotting of task performance score (VFDB1) correlated with the [visuospatial/executive] subtest score on the Montreal Cognitive Assessment (MoCA) scale (Spearman rank correlation coefficient [R] = 0.472, p < 0.001). Conclusion: The dCDT is a tool that can rapidly and accurately characterize and quantify differences in cognitive functioning in AD-MCI and PD-MCI populations.
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页数:19
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