Global trends and prospects of ocular biomarkers in Alzheimer's disease: a bibliometric analysis

阿尔茨海默病眼部生物标志物的全球趋势和前景:文献计量分析

阅读:2

Abstract

BACKGROUND: Alzheimer's disease (AD) diagnosis necessitates the development of novel biomarkers that ensure high diagnostic accuracy and cost-effectiveness in blood tests. Recent studies have identified a significant association between ocular symptoms and the pathological processes of AD, suggesting the potential for effective ocular biomarkers. This bibliometric analysis aims to explore recent advancements and research trends in ocular biomarkers for the early diagnosis of AD. METHODS: Articles related to AD and ocular biomarkers were retrieved from the Web of Science Core Collection (WoSCC) database. These articles were analyzed using bibliometric tools such as VOSviewer, R-bibliometrix, and CiteSpace. RESULTS: A total of 623 papers were included in the analysis, revealing a steady increase in publications since 2012. The United States produced the most publications, followed by China and Italy. Notably, authors affiliated with Complutense University of Madrid in Spain and Sapienza University of Rome in Italy made significant contributions, demonstrating robust internal collaborations. The Journal of Alzheimer's Disease published the most articles pertaining to ocular science and neuroscience. Keyword analysis indicates evolving trends in ocular markers for AD from 2005 to 2024, transitioning from diagnostic techniques (e.g., "spectroscopy," "cerebrospinal fluid") to pathological mechanisms (e.g., "oxidative stress") and advanced imaging technologies (e.g., "optical coherence tomography angiography"). CONCLUSION: The bibliometric analysis highlights key research hotspots related to ocular markers for AD, documenting the shift from basic diagnostic techniques to advanced imaging methods and the discovery of novel biomarkers. Future research may investigate the potential of Optical Coherence Tomography Angiography, tear component analysis, eye movement assessments, and artificial intelligence to enhance early detection of AD.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。