Memory nurses could soon administer a tablet-based cognitive test to spot the earliest signs of Alzheimer’s disease, long before memory loss becomes obvious. Current NHS cognitive assessments miss the subtle mental changes that occur in preclinical Alzheimer’s, and there are too few specialist psychologists to administer more sensitive tests. This project aims to fill that gap by co-developing a computerised assessment tool—CoCoA-PAD—designed specifically for non-psychologist staff in memory clinics. The researchers will test 98 older adults with subjective cognitive difficulties, comparing their CoCoA-PAD scores with blood biomarkers (pTau217) and brain scans to see whether the test can reliably detect early Alzheimer’s pathology and track cognitive decline over one year. If successful, CoCoA-PAD could become a regulated digital health technology that enables earlier diagnosis in routine NHS care. Earlier detection would allow patients to access support and potential treatments sooner, and could help clinical services manage growing demand without requiring more specialist staff. The project also lays the groundwork for a larger funding bid to turn the prototype into a fully approved medical app.
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Background. Alzheimer's disease (AD) is the most common cause of dementia. The accurate diagnosis of preclinical AD is an international priority. Cognitive assessments are a core component of this clinical diagnosis. However, the cognitive fingerprint of early AD is very subtle, and the tests available to clinicians in the NHS are not fit for purpose. Additionally, there are severe staff shortages which threaten our ability to diagnose preclinical AD in the NHS. I have developed a prototype of the Computerised Cognitive Assessment for Preclinical Alzheimer's Disease (CoCoA-PAD), a collection of the best available assessment paradigms designed specifically around the cognitive neurology of preclinical AD. This assessment is designed to be administered by Memory Nurses and has been designed for implementation into NHS services. Aims and Objectives The long-term aim of this research is to develop CoCoA-PAD into an assessment app which meets the regulatory requirements as a health technology for use in the NHS by non-psychologist memory staff. I have developed three short-term work-packages (WP) to support with the long-term aim. The co-creation of CoCoA-PAD with older adults, memory nurses and neuropsychologists. Co-developing a cognitive assessment training protocol for non-specialist NHS staff in memory services and neurorehabilitation Completing an evaluation of CoCoA-PAD psychometric properties. Research question. There are three research questions: Can the CoCoA-PAD subtests detect the earliest cognitive difficulties of AD? Are the CoCoA-PAD subtests sensitive at measuring the health of key brain regions affected earliest in AD? Are the CoCoA-PAD subtests sensitive at measuring cognitive deterioration in people with preclinical AD? Methods This study will include 98 older adults (>70 years) with subjective cognitive difficulties, who are at risk of AD. All participants will receive a cognitive assessment (CoCoA-PAD) and AD biomarker test (pTau217). To establish whether CoCoA-PAD is sensitive and specific to early AD cognitive difficulties, a between-group diagnostic accuracy design will be used. The performance on CoCoA-PAD tests of people with and without AD (based by pTau217) will be compared statistically. A cross-sectional subset of participants (n=59) will have a magnetic resonance imaging (MRI) scan. CoCoA-PAD performance will be compared with volumetric and diffusion metrics of key AD related regions-of-interest using MRI scans. Finally, a subset of participants will be followed up longitudinally, and reassessed one year later (n=36). This study will test whether CoCoA-PAD is sensitive to cognitive decline caused by AD. Timelines for delivery Months 0-6: Ethics, Co-development of CoCoA-PAD, PPI Input, Finalise database and MRI sequence, and open research sites. Months 6-26: Recruitment of sample (n=98) Months 27: Diagnostic confirmation Months 28-30: Follow-up assessment (n=36) Months 31-40: Collate data, data analysis, write up, and dissemination. Anticipated impact and dissemination Short-term impact activities will include academic publications, video abstracts, infographics, and international conference presentations. These will be used to make the case for large-scale onward funding, e.g., NIHR Invention for Innovation (i4i) funding. This funding will be used to develop CoCoA-PAD into an app which meets the requirements to be used as a Tier C Digital Health Technology to Inform Clinical Management.
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