American journal of Alzheimer's disease and other dementias最新文献

Risk Factors Profile in Dementia Patients at a Tertiary Care Hospital in Nepal: A Cross-Sectional Study. 尼泊尔三级医院痴呆患者的危险因素概况：一项横断面研究

American journal of Alzheimer's disease and other dementias Pub Date : 2025-01-01 Epub Date: 2025-03-23 DOI: 10.1177/15333175251328472

Omkar Dhungel, Pawan Sharma, Nidesh Sapkota

引用次数: 0

Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models. 使用决策树模型预测和评估老年人的认知状态。

American journal of Alzheimer's disease and other dementias Pub Date : 2025-01-01 Epub Date: 2025-05-05 DOI: 10.1177/15333175251339730

Zhidi Luo, Stella Ping Wang, Emily H Ho, Lihua Yao, Richard C Gershon

{"title":"Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models.","authors":"Zhidi Luo, Stella Ping Wang, Emily H Ho, Lihua Yao, Richard C Gershon","doi":"10.1177/15333175251339730","DOIUrl":"https://doi.org/10.1177/15333175251339730","url":null,"abstract":"Objective: To improve the identification of cognitive impairment by distinguishing normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer's disease (AD). Methods: A recursive partitioning tree model was developed using ARMADA data and the NIH Toolbox, a multidimensional health assessment tool. It incorporated demographic and clinical assessment variables to predict NC, MCI, and AD. Model performance was evaluated using AUC, precision, recall, and F1 score. Robustness was tested through 5-fold cross-validation, sensitivity, scenario, and subgroup analyses. Results: The model achieved macro-AUC and micro-AUC scores of 0.92 and 0.91 (training) and 0.89 and 0.86 (testing). Key predictors included the Picture Sequence Memory Test and List Sorting Working Memory Test. Cross-validation yielded 70.22% accuracy and a Kappa of 0.52. Conclusion: Machine learning effectively uses a small set of assessments to distinguish NC, MCI, and AD, offering a valuable tool to support clinical decision-making. Future research should validate this model across diverse populations.","PeriodicalId":93865,"journal":{"name":"American journal of Alzheimer's disease and other dementias","volume":"40 ","pages":"15333175251339730"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12056332/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144045933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic Detection of Cognitive Impairment in Patients With White Matter Hyperintensity Using Deep Learning and Radiomics. 利用深度学习和放射组学自动检测白质高强度患者的认知障碍。

American journal of Alzheimer's disease and other dementias Pub Date : 2025-01-01 Epub Date: 2025-03-14 DOI: 10.1177/15333175251325091

Junbang Feng, Xingyan Le, Li Li, Lin Tang, Yuwei Xia, Feng Shi, Yi Guo, Yueqin Zhou, Chuanming Li

{"title":"Automatic Detection of Cognitive Impairment in Patients With White Matter Hyperintensity Using Deep Learning and Radiomics.","authors":"Junbang Feng, Xingyan Le, Li Li, Lin Tang, Yuwei Xia, Feng Shi, Yi Guo, Yueqin Zhou, Chuanming Li","doi":"10.1177/15333175251325091","DOIUrl":"10.1177/15333175251325091","url":null,"abstract":"White matter hyperintensity (WMH) is associated with cognitive impairment. In this study, 79 patients with WMH from hospital 1 were randomly divided into a training set (62 patients) and an internal validation set (17 patients). In addition, 29 WMH patients from hospital 2 were used as an external validation set. Cognitive status was determined based on neuropsychological assessment results. A deep learning convolutional neural network of VB-Nets was used to automatically identify and segment whole-brain subregions and WMH. The PyRadiomics package in Python was used to automatically extract radiomic features from the WMH and bilateral hippocampi. Delong tests revealed that the random forest model based on combined features had the best performance for the detection of cognitive impairment in WMH patients, with an AUC of 0.900 in the external validation set. Our results provide clinical doctors with a reliable tool for the early diagnosis of cognitive impairment in WMH patients.","PeriodicalId":93865,"journal":{"name":"American journal of Alzheimer's disease and other dementias","volume":"40 ","pages":"15333175251325091"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11909688/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143631117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Alzheimer's Disease Dementia Prevalence in the United States: A County-Level Spatial Machine Learning Analysis. 美国阿尔茨海默病痴呆患病率：县级空间机器学习分析。

American journal of Alzheimer's disease and other dementias Pub Date : 2025-01-01 Epub Date: 2025-04-21 DOI: 10.1177/15333175251335570

Abolfazl Mollalo, George Grekousis, Hermes Florez, Brian Neelon, Leslie A Lenert, Alexander V Alekseyenko

{"title":"Alzheimer's Disease Dementia Prevalence in the United States: A County-Level Spatial Machine Learning Analysis.","authors":"Abolfazl Mollalo, George Grekousis, Hermes Florez, Brian Neelon, Leslie A Lenert, Alexander V Alekseyenko","doi":"10.1177/15333175251335570","DOIUrl":"https://doi.org/10.1177/15333175251335570","url":null,"abstract":"A growing body of literature has examined the impact of neighborhood characteristics on Alzheimer's disease (AD) dementia, yet the spatial variability and relative importance of the most influential factors remain underexplored. We compiled various widely recognized factors to examine spatial heterogeneity and associations with AD dementia prevalence via geographically weighted random forest (GWRF) approach. The GWRF outperformed conventional models with an out-of-bag R2 of 74.8% in predicting AD dementia prevalence and the lowest error (MAE = 0.34, RMSE = 0.45). Key findings showed that mobile homes were the most influential factor in 19.9% of U.S. counties, followed by NDVI (17.4%), physical inactivity (12.9%), households with no vehicle (11.3%), and particulate matter (10.4%), while other primary factors affecting <10% of U.S. counties. Findings highlight the need for county-specific interventions tailored to local risk factors. Policies should prioritize increasing affordable housing stability, expanding green spaces, improving transportation access, promoting physical activity, and reducing air pollution exposure.","PeriodicalId":93865,"journal":{"name":"American journal of Alzheimer's disease and other dementias","volume":"40 ","pages":"15333175251335570"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144002030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Restoration of Memory Along With Neurogenic Enhancement by Therapeutic Botulinum Neurotoxin in a Preclinical Model of Parkinson's Disease. 在帕金森病临床前模型中，治疗性肉毒杆菌神经毒素对记忆恢复和神经源性增强的影响

American journal of Alzheimer's disease and other dementias Pub Date : 2025-01-01 Epub Date: 2025-05-30 DOI: 10.1177/15333175251346292

Jerly Helan Mary Joseph, Mahesh Kandasamy

{"title":"Restoration of Memory Along With Neurogenic Enhancement by Therapeutic Botulinum Neurotoxin in a Preclinical Model of Parkinson's Disease.","authors":"Jerly Helan Mary Joseph, Mahesh Kandasamy","doi":"10.1177/15333175251346292","DOIUrl":"10.1177/15333175251346292","url":null,"abstract":"Parkinson's disease (PD) is characterized by degeneration of dopaminergic neurons in the substantia nigra (SN), leading to motor impairments, while hippocampal dysfunction contributes to memory deficits. Botulinum neurotoxin (BoNT), a therapeutic modulator of acetylcholine (ACh) release, its cognitive effects remain underexplored. We investigated the effect of BoNT on spatial learning, memory, microglia and hippocampal neurogenesis in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model of PD. Behavioral tests, including the open field, novel object recognition, and Morris water maze, demonstrated significant improvements in locomotion, learning, and memory with BoNT treatment. BoNT increased the number of doublecortin (DCX)-positive immature neurons and percentage of bromodeoxyuridine (BrdU)/neuronal nuclei (NeuN) double-positive cells, while the reduced number of microglia was evident in the hippocampal dentate gyrus (DG). Additionally, histological analyses revealed BoNT-mediated protection of pyramidal neurons in hippocampal cornu ammonis (CA)-1 and CA3 regions. These findings suggest that BoNT mitigates memory deficits by promoting neurogenesis in experimental PD.","PeriodicalId":93865,"journal":{"name":"American journal of Alzheimer's disease and other dementias","volume":"40 ","pages":"15333175251346292"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12126647/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144188625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Birth Rate as a Determinant of Dementia Incidence: A Comprehensive Global Analysis. 出生率是痴呆发病率的决定因素：一项全面的全球分析。

American journal of Alzheimer's disease and other dementias Pub Date : 2025-01-01 DOI: 10.1177/15333175241287677

Wenpeng You

{"title":"Birth Rate as a Determinant of Dementia Incidence: A Comprehensive Global Analysis.","authors":"Wenpeng You","doi":"10.1177/15333175241287677","DOIUrl":"10.1177/15333175241287677","url":null,"abstract":"Background: The role of parity in predicting dementia risk in women is debated. This study examines how birth rate affects global dementia incidence.Methods: Country-specific data on birth rate and dementia incidence rate were analyzed using bivariate analysis, partial correlation, and multiple linear regression. Confounding factors such as aging, affluence, genetic predisposition (Ibs), and urbanization were considered.Results: Pearson's r and nonparametric analyzes showed a significant inverse correlation between birth rate and dementia incidence. This relationship remained significant after controlling for aging, affluence, Ibs, and urbanization. Multiple linear regression identified birth rate as a significant predictor of dementia incidence, and as the strongest predictor. Affluence and urbanization were not significant predictors. The correlation was stronger in developing countries.Conclusions: Lower birth rate is an independent risk factor for dementia, particularly in developed countries. These findings highlight the importance of considering birth rate in dementia studies.","PeriodicalId":93865,"journal":{"name":"American journal of Alzheimer's disease and other dementias","volume":"40 ","pages":"15333175241287677"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11775964/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143061739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study on Effect of Different Pulses of rTMS on Visual Working Memory in Elderly With SCD. 不同脉冲rTMS对老年SCD患者视觉工作记忆影响的研究。

American journal of Alzheimer's disease and other dementias Pub Date : 2025-01-01 Epub Date: 2025-03-13 DOI: 10.1177/15333175251322351

Liu Meng, Ren-Ren Li, Zhang Wei, Janelle Si Yi Yeo, Jia-Xin Yan, XueKeEr BuMaYiLaMu, Tu Zhao-Xi, Li Yun-Xia

引用次数: 0

Identification of Dementia & Mild Cognitive Impairment in Chinese Elderly Using Machine Learning. 利用机器学习识别中国老年人的痴呆症和轻度认知障碍。

American journal of Alzheimer's disease and other dementias Pub Date : 2024-01-01 DOI: 10.1177/15333175241275215

Tong-Tong Ying, Li-Ying Zhuang, Shan-Hu Xu, Shu-Feng Zhang, Li-Jun Huang, Wei-Wei Gao, Lu Liu, Qi-Lun Lai, Yue Lou, Xiao-Li Liu

{"title":"Identification of Dementia & Mild Cognitive Impairment in Chinese Elderly Using Machine Learning.","authors":"Tong-Tong Ying, Li-Ying Zhuang, Shan-Hu Xu, Shu-Feng Zhang, Li-Jun Huang, Wei-Wei Gao, Lu Liu, Qi-Lun Lai, Yue Lou, Xiao-Li Liu","doi":"10.1177/15333175241275215","DOIUrl":"10.1177/15333175241275215","url":null,"abstract":"Objective: To assess the role of Machine Learning (ML) in identification critical factors of dementia and mild cognitive impairment.Methods: 371 elderly individuals were ultimately included in the ML analysis. Demographic information (including gender, age, parity, visual acuity, auditory function, mobility, and medication history) and 35 features from 10 assessment scales were used for modeling. Five machine learning classifiers were used for evaluation, employing a procedure involving feature extraction, selection, model training, and performance assessment to identify key indicative factors.Results: The Random Forest model, after data preprocessing, Information Gain, and Meta-analysis, utilized three training features and four meta-features, achieving an area under the curve of 0.961 and a accuracy of 0.894, showcasing exceptional accuracy for the identification of dementia and mild cognitive impairment.Conclusions: ML serves as a identification tool for dementia and mild cognitive impairment. Using Information Gain and Meta-feature analysis, Clinical Dementia Rating (CDR) and Neuropsychiatric Inventory (NPI) scale information emerged as crucial for training the Random Forest model.","PeriodicalId":93865,"journal":{"name":"American journal of Alzheimer's disease and other dementias","volume":"39 ","pages":"15333175241275215"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11320688/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141918304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and Validation of an Automatic Computerized Neurocognitive Battery in Chinese. 中文自动计算机化神经认知测验的开发与验证。

American journal of Alzheimer's disease and other dementias Pub Date : 2024-01-01 DOI: 10.1177/15333175241271910

Ji Zhang, Ze-Yu Hong, Liu Yang, Xiao-Jia Li, Fang Ye

{"title":"Development and Validation of an Automatic Computerized Neurocognitive Battery in Chinese.","authors":"Ji Zhang, Ze-Yu Hong, Liu Yang, Xiao-Jia Li, Fang Ye","doi":"10.1177/15333175241271910","DOIUrl":"10.1177/15333175241271910","url":null,"abstract":"Objectives: Neuropsychological test batteries, which accurately and comprehensively assess cognitive functions, are a crucial approach in the early detection of and interventions for cognitive impairments. However, these tests have yet to gain wide clinical application in China owing to their complexity and time-consuming nature. This study aimed to develop the Computerized Neurocognitive Battery for Chinese-Speaking participants (CNBC), an autorun and autoscoring cognitive assessment tool to provide efficient and accurate cognitive evaluations for Chinese-Speaking individuals.Methods: The CNBC was developed through collaboration between clinical neurologists and software engineers. Qualified volunteers were recruited to complete CNBC and traditional neurocognitive batteries. The reliability and validity of the CNBC were evaluated by analyzing the correlations between the measurements obtained from the computerized and the paper-based assessment and those between software-based scoring and manual scoring.Results: The CNBC included 4 subtests and an autorun version. Eighty-six volunteers aged 51-82 years with 7-22 years of education were included. Significant correlations (0.256-0.666) were observed between paired measures associated with attention, executive function, and episodic memory from the CNBC and the traditional paper-based neurocognitive batteries. This suggests a strong construct validity of the CNBC in assessing these cognitive domains. Furthermore, the correlation coefficients between manual scoring and system scoring ranged from 0.904-1.0, indicating excellent inter-rater reliability for the CNBC.Interpretation: A novel CNBC equipped with automated testing and scoring features was developed in this study. The preliminary results confirm its strong reliability and validity, indicating its promising potential for clinical utilization.","PeriodicalId":93865,"journal":{"name":"American journal of Alzheimer's disease and other dementias","volume":"39 ","pages":"15333175241271910"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11457180/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142376416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neuropsychiatric Behavioral Assessments in Mice After Acute and Long-Term Treatments of Low-Intensity Pulsed Ultrasound. 低强度脉冲超声波急性和长期治疗后的小鼠神经精神行为评估

American journal of Alzheimer's disease and other dementias Pub Date : 2024-01-01 DOI: 10.1177/15333175231222695

Ye Li, Yiqing Wu, Qi Luo, Xuanjie Ye, Jie Chen, Yuanlin Su, Ke Zhao, Xinmin Li, Jing Lin, Zhiqian Tong, Qi Wang, Dongwu Xu

{"title":"Neuropsychiatric Behavioral Assessments in Mice After Acute and Long-Term Treatments of Low-Intensity Pulsed Ultrasound.","authors":"Ye Li, Yiqing Wu, Qi Luo, Xuanjie Ye, Jie Chen, Yuanlin Su, Ke Zhao, Xinmin Li, Jing Lin, Zhiqian Tong, Qi Wang, Dongwu Xu","doi":"10.1177/15333175231222695","DOIUrl":"10.1177/15333175231222695","url":null,"abstract":"Introduction: To evaluate whether both acute and chronic low-intensity pulsed ultrasound (LIPUS) affect brain functions of healthy male and female mice. Methods: Ultrasound (frequency: 1.5 MHz; pulse: 1.0 kHz; spatial average temporal average (SATA) intensity: 25 mW/cm2; and pulse duty cycle: 20%) was applied at mouse head in acute test for 20 minutes, and in chronic experiment for consecutive 10 days, respectively. Behaviors were then evaluated. Results: Both acute and chronic LIPUS at 25 mW/cm2 exposure did not affect the abilities of movements, mating, social interaction, and anxiety-like behaviors in the male and female mice. However, physical restraint caused struggle-like behaviors and short-time memory deficits in chronic LIPUS groups in the male mice. Conclusion: LIPUS at 25 mW/cm2 itself does not affect brain functions, while physical restraint for LIPUS therapy elicits struggle-like behaviors in the male mice. An unbound helmet targeted with ultrasound intensity at 25-50 mW/cm2 is proposed for clinical brain disease therapy.","PeriodicalId":93865,"journal":{"name":"American journal of Alzheimer's disease and other dementias","volume":"39 ","pages":"15333175231222695"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10771054/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139106995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0