Title: Predicting long-term incidence of new-onset dementia using primary and secondary care data from Electronic Health Records
Speakers: Konstantin Georgiev
Abstract:

Dementia is a devastating and frequently life-limiting condition, which affects over 90,000 older people in Scotland. While there are no cures available, recent scientific breakthroughs suggest the potential to further slow dementia progression, but these medications are likely to be needed very early in the condition. A recent surge in studies incorporating routine data to predict incidence of dementia has aided in this risk assessment, but a lot of these are selectively biased to include people with pre-existing cognitive impairments and episodes of memory loss. In this longitudinal study, my objective is to provide an inclusive community-level risk assessment, exploring the effects of demographic and lifestyle factors linked with medical and comorbidity history on incidence of dementia. In this talk, I will share some of the key stages of developing and validating a supervised Machine Learning tool for identifying people at risk of new-onset dementia at 5 and 10 years over a large NHS Lothian population. Given the complexity of dementia, this approach is unlikely to provide perfect diagnostic performance at individual-level predictions, but even just identifying groups with substantially higher than average long-term risk can aid in controlling for these risk factors through preventative interventions and drug therapy.