Predicting dementia outcomes using simple, non-invasive assessments
Principal Investigator:
Dr Tim Wilkinson
Approved Research ID:
25026
Approval date:
December 19th 2016
Lay summary
We will investigate which factors predict who will subsequently develop dementia. By focusing on simple, readily-available information that might be available to doctors in their everyday practice, we will ultimately be able to develop a series of models that combine these variables to predict who is at risk of dementia over a 5-10 year period. This research aims to improve our ability to prevent dementia. The processes underlying dementia begin in middle age, and so preventative treatments or lifestyle interventions should be targeted to this age group, in order to have an impact in later life. By developing a dementia risk prediction model we will be able to identify who, in an asymptomatic population, is at the highest risk of developing dementia in the future. These people can then be identified for treatment or recruited into intervention trials. We will look at the predictive value of chosen variables independently to identify which variables are most predictive, focusing on variables that are likely to be available to clinicians in daily practice, e.g. age, family history, vascular risk, medical history and simple blood tests (e.g. kidney function). We will then combine the most predictive variables into a model. Full cohort - all 503,000 participants