Using astrophysics to close the “diagnosis gap” for dementia in UK general practice
Study Code / Acronym
ASTRODEMAward Number
202133/Z/16/ZAward Type
Seed Awards in ScienceStatus / Stage
CompletedDates
1 October 2016 -31 March 2019
Duration (calculated)
02 years 05 monthsFunder(s)
Wellcome TrustFunding Amount
£94,008.00Funder/Grant study page
Wellcome TrustContracted Centre
University of SussexContracted Centre Webpage
Principal Investigator
Dr Elizabeth FordPI Contact
E.M.Ford@bsms.ac.ukPI ORCID
0000-0001-5613-8509WHO Catergories
Development of clinical assessment of cognition and functionMethodologies and approaches for risk reduction research
Disease Type
Dementia (Unspecified)CPEC Review Info
| Reference ID | 306 |
|---|---|
| Researcher | Reside Team |
| Published | 12/06/2023 |
Data
| Study Code / Acronym | ASTRODEM |
|---|---|
| Award Number | 202133/Z/16/Z |
| Status / Stage | Completed |
| Start Date | 20161001 |
| End Date | 20190331 |
| Duration (calculated) | 02 years 05 months |
| Funder/Grant study page | Wellcome Trust |
| Contracted Centre | University of Sussex |
| Contracted Centre Webpage | |
| Funding Amount | £94,008.00 |
Abstract
Dementia is one of the greatest public health challenges of our era. Timely diagnosis allows patients to benefit from current therapies, plan for the future, and maximise their quality of life. However, there is a “diagnosis gap” in UK general practice, with less than two-thirds of expected patients receiving a dementia diagnosis. Increasing diagnosis rates is a strategic aim of the UK government and NHS.
Aims
We aim to close this diagnosis gap in a novel collaboration between primary care epidemiology and astrophysics. We will use a very large set of UK general practice electronic patient records (96,000 patients; 50% with dementia) spanning up to 10 years per patient. We will use a probabilistic programming framework to apply statistical techniques to model dementia onset in this cohort, allowing for the inherent variability and duration of disease development. To achieve a clinically valuable model, these multi-dimensional data will require sophisticated analysis techniques that are not currently available in medical statistics and epidemiology, but which astrophysicists use daily.
Our goal is to develop a statistical model to predict risk of dementia from patients’ general practice records, which will help GPs and other NHS bodies better estimate and identify cases in UK general practice.