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[Preprint]. 2024 Feb 13:2024.02.10.24302621.
doi: 10.1101/2024.02.10.24302621.

Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data

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Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data

Aokun Chen et al. medRxiv. .

Abstract

A comprehensive view of factors associated with AD/ADRD will significantly aid in studies to develop new treatments for AD/ADRD and identify high-risk populations and patients for prevention efforts. In our study, we summarized the risk factors for AD/ADRD by reviewing existing meta-analyses and review articles on risk and preventive factors for AD/ADRD. In total, we extracted 477 risk factors in 10 categories from 537 studies. We constructed an interactive knowledge map to disseminate our study results. Most of the risk factors are accessible from structured Electronic Health Records (EHRs), and clinical narratives show promise as information sources. However, evaluating genomic risk factors using RWD remains a challenge, as genetic testing for AD/ADRD is still not a common practice and is poorly documented in both structured and unstructured EHRs. Considering the constantly evolving research on AD/ADRD risk factors, literature mining via NLP methods offers a solution to automatically update our knowledge map.

Keywords: Alzheimer’s Disease and Related Dementia; Natural Language Processing.

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Figures

Figure 1.
Figure 1.
The overall workflow of the study.
Figure 2.
Figure 2.
Our overall literature search and review procedure according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram.
Figure 3.
Figure 3.
An overview of the knowledge graph for AD-related risk factors.
Figure 4.
Figure 4.
Demographic and environmental risk factors for AD: (a) illustrates that age is a risk factor of AD, and (b) illustrates that exposure to pesticide does not have significant effect on AD.
Figure 5.
Figure 5.
Relation between brain trauma and dementia mined from literature via natural language process methods.

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