AD-MCI和PD-MCI人群在数字时钟绘制测试中的差异认知功能。

IF 3.2 3区 医学 Q2 NEUROSCIENCES
Frontiers in Neuroscience Pub Date : 2025-03-13 eCollection Date: 2025-01-01 DOI:10.3389/fnins.2025.1558448
Chen Wang, Kai Li, Shouqiang Huang, Jiakang Liu, Shuwu Li, Yuting Tu, Bo Wang, Pengpeng Zhang, Yuntian Luo, Tong Chen
{"title":"AD-MCI和PD-MCI人群在数字时钟绘制测试中的差异认知功能。","authors":"Chen Wang, Kai Li, Shouqiang Huang, Jiakang Liu, Shuwu Li, Yuting Tu, Bo Wang, Pengpeng Zhang, Yuntian Luo, Tong Chen","doi":"10.3389/fnins.2025.1558448","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 (<i>VFDB</i> <sub>1</sub>) correlated with the [visuospatial/executive] subtest score on the Montreal Cognitive Assessment (MoCA) scale (Spearman rank correlation coefficient [R] = 0.472, <i>p</i> < 0.001).</p><p><strong>Conclusion: </strong>The dCDT is a tool that can rapidly and accurately characterize and quantify differences in cognitive functioning in AD-MCI and PD-MCI populations.</p>","PeriodicalId":12639,"journal":{"name":"Frontiers in Neuroscience","volume":"19 ","pages":"1558448"},"PeriodicalIF":3.2000,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11965901/pdf/","citationCount":"0","resultStr":"{\"title\":\"Differential cognitive functioning in the digital clock drawing test in AD-MCI and PD-MCI populations.\",\"authors\":\"Chen Wang, Kai Li, Shouqiang Huang, Jiakang Liu, Shuwu Li, Yuting Tu, Bo Wang, Pengpeng Zhang, Yuntian Luo, Tong Chen\",\"doi\":\"10.3389/fnins.2025.1558448\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 (<i>VFDB</i> <sub>1</sub>) correlated with the [visuospatial/executive] subtest score on the Montreal Cognitive Assessment (MoCA) scale (Spearman rank correlation coefficient [R] = 0.472, <i>p</i> < 0.001).</p><p><strong>Conclusion: </strong>The dCDT is a tool that can rapidly and accurately characterize and quantify differences in cognitive functioning in AD-MCI and PD-MCI populations.</p>\",\"PeriodicalId\":12639,\"journal\":{\"name\":\"Frontiers in Neuroscience\",\"volume\":\"19 \",\"pages\":\"1558448\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2025-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11965901/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fnins.2025.1558448\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fnins.2025.1558448","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

背景:轻度认知障碍(MCI)在阿尔茨海默病(AD)和帕金森病(PD)中很常见,但阿尔茨海默病所致轻度认知障碍(AD-MCI)和帕金森病合并轻度认知障碍(PD-MCI)人群在发病机制和认知表现上存在差异。研究表明,基于数字时钟绘制测试(dCDT)的评估可以有效地反映认知缺陷。基于此,我们提出以下研究假设:AD-MCI和PD-MCI人群在CDT的认知功能上存在差异,基于这一特征可以有效区分这两个人群。方法:为了验证这一假设,我们设计了dCDT来提取能够表征和量化AD-MCI和PD-MCI人群之间认知功能差异的数字生物标志物。我们共入组了40例 AD-MCI患者、40例PD- mci患者、41例PD认知正常(PD-NC)患者和40例正常认知(NC)对照。结果:通过横断面研究,我们发现AD-MCI和PD-MCI人群在dCDT中的认知功能存在差异,将AD-MCI与PD-MCI患者区分开来,roc曲线下面积(AUC) = 0.923,95%置信区间(CI) = 0.866-0.983。高学历(≥12 年)AD-MCI与PD-MCI患者有效鉴别的AUC为0.968,CI = 0.927-1.000。通过相关分析,我们发现任务表现总分(VFDB 1)与蒙特利尔认知评估量表(MoCA)[视觉空间/执行]子测试得分相关(Spearman rank correlation coefficient [R] = 0.472,p )。结论:dCDT可以快速、准确地表征和量化AD-MCI和PD-MCI人群的认知功能差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Differential cognitive functioning in the digital clock drawing test in AD-MCI and PD-MCI populations.

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 (VFDB 1) 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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Frontiers in Neuroscience
Frontiers in Neuroscience NEUROSCIENCES-
CiteScore
6.20
自引率
4.70%
发文量
2070
审稿时长
14 weeks
期刊介绍: Neural Technology is devoted to the convergence between neurobiology and quantum-, nano- and micro-sciences. In our vision, this interdisciplinary approach should go beyond the technological development of sophisticated methods and should contribute in generating a genuine change in our discipline.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信