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Accurate diagnosis and prognosis of Alzheimer’s disease in primary care

Objective

The overall objective of ADetect is to improve early diagnostics and prognostics of Alzheimer's disease in primary care by utilising novel plasma biomarkers and digital cognitive tests. Misdiagnosis of AD can reach >50% in primary care, which has important consequences both at the personal and societal level. Misdiagnosis, however, can be reduced by measuring AD-related pathology. The novel plasma biomarkers may be a cost-effective alternative given their low invasiveness and costs. However, they have not been validated in primary care yet, where much more diverse groups of people are managed. Further, the addition of brief cognitive digital tests that do not require involvement of a specialist may further improve the diagnostic accuracy. Based on the most cost-effective biomarkers, collected in unique prospective study performed in primary care, we will develop algorithms for diagnosis and prognosis of AD in a diverse population, and share them in the form of open and freely available apps. The algorithms will be validated against current standard of truth biomarkers and enhanced to give personalized risk assessments based on patient’s characteristics. Finally, we will investigate whether prospective use of these algorithms will improve treatment, management and care of patients. The development of easy-to-use tools, built on novel cognitive tests and plasma biomarkers, has huge potential to increase the diagnostic accuracy in primary care. A more accurate and timely diagnosis will lead to earlier initiation of currently available AD treatments. Further, when disease-modifying treatments become globally available, there will be an immense pressure on the healthcare system to identify eligible patients. Given the high prevalence of AD, its identification will primarily take place in primary care. With the easy-available proposed biomarkers, we have a great opportunity to develop the necessary tools for primary care to undertake this important task

Coordinator

LUNDS UNIVERSITET
Net EU contribution
€ 206 887,68
Address
Paradisgatan 5c
22100 Lund
Sweden

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Region
Södra Sverige Sydsverige Skåne län
Activity type
Higher or Secondary Education Establishments
Other funding
No data