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ORIGINAL RESEARCH article
Front. Neurosci.
Sec. Neurodegeneration
Volume 19 - 2025 | doi: 10.3389/fnins.2025.1558448
This article is part of the Research Topic Advancing personalized diagnosis and treatment in Parkinson's Disease: Integrating biomarkers, neuroimaging, and artificial intelligence View all 4 articles
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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. 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. 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). Thus, the dCDT is a tool that can rapidly and accurately characterize and quantify differences in cognitive functioning in AD-MCI and PD-MCI populations.
Keywords: Alzheimer's disease, Parkinson's disease, Mild Cognitive Impairment, digital clock drawing test, Cognitive Function, digital biomarkers
Received: 10 Jan 2025; Accepted: 26 Feb 2025.
Copyright: © 2025 Wang, Li, Huang, Liu, Li, Tu, Wang, Zhang, Luo and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Kai Li, School of Information Engineering, Hangzhou Medical College, Hangzhou, Jiangsu Province, China
Tong Chen, Department of Neurology, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
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