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Lookup NU author(s): Dr Eugene TangORCiD, Dr John Brain, Dr Eduwin PakpahanORCiD, Professor Dame Louise Robinson, Dr Mario Siervo, Professor Bloss Stephan
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 by the authors. Dementia is a leading cause of disability and death globally. Individuals with diseases such as cardiovascular, cardiometabolic and cerebrovascular disease are often at increased dementia risk. However, while numerous models have been developed to predict dementia, they are often not tailored to disease-specific groups. Yet, different disease groups may have unique risk factor profiles and tailored models that account for these differences may have enhanced predictive accuracy. In this review, we synthesise findings from three previous systematic reviews on dementia risk model development and testing to present an overview of the literature on dementia risk prediction modelling in people with a history of disease. Nine studies met the inclusion criteria. Currently, disease-specific models have only been developed in people with a history of diabetes where demographic, disease-specific and comorbidity data were used. Some existing risk models, including CHA2DS2-VASc and CHADS2, have been externally validated for dementia outcomes in those with atrial fibrillation and heart failure. One study developed a dementia risk model for their whole population, which had similar predictive accuracy when applied in a sub-sample with stroke. This emphasises the importance of considering disease status in identifying key predictors for dementia and generating accurate prediction models for dementia.
Author(s): Tang EYH, Brain J, Sabatini S, Pakpahan E, Robinson L, Alshahrani M, Naheed A, Siervo M, Stephan BCM
Publication type: Review
Publication status: Published
Journal: Life
Year: 2024
Volume: 14
Issue: 11
Online publication date: 15/11/2024
Acceptance date: 12/11/2024
ISSN (electronic): 2075-1729
Publisher: MDPI
URL: https://doi.org/10.3390/life14111489
DOI: 10.3390/life14111489
Data Access Statement: All data contained within this article are available from our previously published systematic reviews.
