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Understanding the Aging and Age-Related Neurological Disease

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Guest Editor
Artificial Intelligence Center, China Medical University Hospital, Taichung 404327, Taiwan
Interests: medical artificial intelligence; digital health; dementia; stroke; sleep disorder; systems biology; bioinformatics

Special Issue Information

Dear Colleagues,

The aging of the global population is a trend that continues to rise, with an increasing number of individuals reaching their golden years. According to the World Health Organization (WHO), it is estimated that over 16% of the world's population will be 65 years of age and older by 2050. This emphasizes the importance of addressing age-related health concerns, including debilitating neurological conditions such as dementia, stroke, and Parkinson's disease. These diseases not only affect patients but also caregivers and families, and they have a far-reaching impact on both the economy and society. 

However, the rapid advancement of genetics, lifestyle factors, digital health, and imaging techniques has greatly increased our understanding of these conditions. In response to this growing public health concern, the International Journal of Environmental Research and Public Health (IJERPH) has issued a call for papers that delve into the intricate relationship between aging and the development of neurological conditions. This provides a platform for authors to contribute to ongoing efforts to improve our understanding of these conditions and develop new therapeutic strategies to enhance the lives of those affected. Please note that clinical studies not sufficiently addressing the aim of the journal will not be considered.

Dr. Kai-Cheng Hsu
Guest Editor

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Keywords

  • aging
  • neurological disease
  • dementia
  • stroke
  • Parkinson’s disease
  • quality of life
  • digital health
  • telemedicine
  • in-home support
  • AI-powered healthcare

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Published Papers (1 paper)

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Research

13 pages, 731 KiB  
Article
Clinical and Neuroimaging Predictors of Alzheimer’s Dementia Conversion in Patients with Mild Cognitive Impairment Using Amyloid Positron Emission Tomography by Quantitative Analysis over 2 Years
by Seonjeong Kim, Daye Yoon, Junho Seong, Young Jin Jeong, Do-Young Kang and Kyung Won Park
Int. J. Environ. Res. Public Health 2024, 21(5), 547; https://doi.org/10.3390/ijerph21050547 - 26 Apr 2024
Viewed by 1259
Abstract
Patients with mild cognitive impairment (MCI) have a relatively high risk of developing Alzheimer’s dementia (AD), so early identification of the risk for AD conversion can lessen the socioeconomic burden. In this study, 18F-Florapronol, newly developed in Korea, was used for qualitative [...] Read more.
Patients with mild cognitive impairment (MCI) have a relatively high risk of developing Alzheimer’s dementia (AD), so early identification of the risk for AD conversion can lessen the socioeconomic burden. In this study, 18F-Florapronol, newly developed in Korea, was used for qualitative and quantitative analyses to assess amyloid positivity. We also investigated the clinical predictors of the progression from MCI to dementia over 2 years. From December 2019 to December 2022, 50 patients with MCI were recruited at a single center, and 34 patients were included finally. Based on visual analysis, 13 (38.2%) of 34 participants were amyloid-positive, and 12 (35.3%) were positive by quantitative analysis. Moreover, 6 of 34 participants (17.6%) converted to dementia after a 2-year follow-up (p = 0.173). Among the 15 participants who were positive for amyloid in the posterior cingulate region, 5 (33.3%) patients developed dementia (p = 0.066). The Clinical Dementia Rating-Sum of Boxes (CDR-SOB) at baseline was significantly associated with AD conversion in multivariate Cox regression analyses (p = 0.043). In conclusion, these results suggest that amyloid positivity in the posterior cingulate region and higher CDR-SOB scores at baseline can be useful predictors of AD conversion in patients with MCI. Full article
(This article belongs to the Special Issue Understanding the Aging and Age-Related Neurological Disease)
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