Dementia has long been considered to be neither preventable nor treatable, but while the underlying illnesses may not be curable, today we know that the disease course might be modifiable with adequate preventive interventions at an early timepoint. The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) showed a positive effect after a 2-year intervention period targeting several lifestyle and vascular risk factors simultaneously. FINGER was the first large randomised controlled trial of its kind demonstrating the possibility of preventing cognitive decline using a multi-domain intervention among older at-risk individuals.
Performing on such a clinical-scientific evidence, new information and communication technology (ICT) and machine learning algorithms can help leveraging daily personalized interventions to prevent dementia and monitoring relevant risk factors. This is the vision of LETHE, an EU project funded by the H2020 programme.
In phase one, the project provides a data-driven risk factor prediction model for older individuals at risk of cognitive decline. This model is based on big data analyses of observational and longitudinal intervention datasets from our four participating European clinical centres.
In the second phase, an ICT-based semi-automated intervention protocol named FINGER 2.0 is provided to people at risk, engaging participants in their individual lifestyle. A prediction model, based on the big data analyses conducted in phase one, provides a machine-learning based approach towards the risk of development of dementia.
Across an intervention trial lasting 24 months, LETHE will establish novel digital biomarkers for early detection of risk factors unobtrusively detected by an ICT-based passive and active monitoring of patient behaviour and lifestyle. The personalized ICT-based preventative lifestyle intervention will support individualised profiling, personalised recommendations, feedback, and support.
Successful conduction of this project will provide the opportunity to demonstrate the effectiveness and efficacy of an ICT based semi-automated and personalized dementia prevention setup in daily life settings of persons at risk of dementia. By including a large study population of at-risk persons, this will result in widely reducing the individual risk profile of participants.
LETHE project aims at contributing to the current knowledge of the disease and the possible influence of different lifestyle factors on dementia progression. The underlying model will help to project and forecast the development of related risk factors. It thereby aims to help address risk early and shift the onset of cognitive decline and / or lower the progression speed. Moreover, the LETHE project is expected to have a long-term effect on the healthcare sector and provide a foundation for health literacy strategies. The project will highlight the necessity for fully design-centred interventions and solutions for the target population at risk. LETHE aims to demonstrate that enhanced risk detection and management tools in the context of cognitive impairment can contribute to increased effectiveness and efficiency in long-term care management of chronic disease affecting 55+ population.
