There are over 850,000 people in the UK living with dementia(1) and though there are currently no cures, early diagnosis is a key priority for the National Health Service (NHS). Presently, the primary purpose of early detection is timely access to information, services, as well as care planning. In the future, any pharmacological intervention would be applied during the early stages of disease development in order to prevent or slow cognitive decline. However, given the chronic and progressive nature of the condition, identifying dementia in its earliest stages is challenging.
Electronic health records provide a complete timeline of an individual’s health, and therefore allow us to investigate how early cognitive decline develops into dementia. In this study, we will use sophisticated analytical approaches to identify and explore what signs and symptoms are recorded in a patient’s electronic health record that could potentially help researchers and clinicians identify the early stages of cognitive decline associated with dementia.
The results of this study will make steps towards maximizing the value and use of routinely collected electronic health record data for early diagnosis of dementia, support identifying high-risk individuals, facilitate research in early-stage dementia and improve dementia care planning.
Objective:
The primary objective of this study is to explore the use of electronic health records to identify clinically significant markers of early cognitive decline (referred to as prodromal markers) associated with dementia. The methods developed through this research project will potentially enable the earlier diagnosis of people with dementia.
Methods & Data analysis:
Part I: Exploratory, hypothesis-generation to examine occurrence and recording patterns of prodromal markers prior to dementia diagnosis. Prodromal markers with the highest frequency, supplemented by clinical expert knowledge and literature of common prodromal markers will be further investigated. Markers in the following clinical categories will be explored: a) activity complementary to dementia diagnosis, b) healthcare utilisation patterns, d) cognitive symptoms, d) motor symptoms, e) affective symptoms, f) autonomic symptoms, g) prescriptions of dementia-specific medication and h) routinely conducted tests when dementia is being investigated.
Part II: Hypothesis-testing, retrospective nested case-control study. We will apply logistic regression to measure the strength of the association between the prodromal markers and diagnosis of dementia across different time periods.
Spiros Denaxas - Chief Investigator - University College London ( UCL )
Spiros Denaxas - Corresponding Applicant - University College London ( UCL )
Kate Walters - Collaborator - University College London ( UCL )
Martin Rossor - Collaborator - University College London ( UCL )
Maxine Mackintosh - Collaborator - University College London ( UCL )
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation