A machine learning method analyzing large amounts of health information has potential in assessing the risk of cognitively healthy older people for later dementia, according to research published in the Journal of Alzheimer’s Disease | ScienceDaily
The research team used data from the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) study conducted in Eastern Finland. Study participants were cognitively normal individuals aged 65-79 years from the general Finnish population who underwent detailed health-related assessments, including memory and other cognitive tests. The dementia risk index performed well in identifying comprehensive profiles for predicting dementia development up to 10 years later. The main included predictors were cognition, vascular factors, age, subjective memory complaints and apolipoprotein E (APOE) genotype.
The researchers conclude that the risk index could be useful for identifying older individuals who are most at risk, and who may also benefit most from preventive interventions. They emphasize that the risk index is not meant for dementia diagnosis, but as a tool to help with making decisions about dementia prevention strategies, i.e. to whom these should be targeted, and what risk factors should be specifically addressed based on the visual risk profile.
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