Clinical Research Directory

Neurocognitive Assessment Platform 4 Alzheimer

The aging population in Europe is leading to an increase in neurodegenerative diseases, such as Alzheimer's disease (AD), which is expected to affect 152 million people worldwide by 2050. In Italy, there are approximately 1.2 million cases of dementia, with 600,000 attributed to AD. Given the limited effectiveness of current pharmacological treatments, there is a growing need for early, non-pharmacological interventions to slow disease progression and improve the quality of life for patients and caregivers. The Neurocognitive Assessment Platform 4 Alzheimer (NAP4A) study aims to create a digital platform for the early detection of amnestic mild cognitive impairment (MCIa), considered an intermediate stage between normal aging and dementia. The platform uses non-invasive biometric tools, including EEG, blood flow sensors, and eye-tracking devices, to collect neurophysiological and behavioral data. The study will involve 100 participants aged 55 to 80, divided into two groups: one with individuals diagnosed with MCIa and a control group of healthy participants. Over 12 months, regular assessments will be conducted to identify markers that predict the progression from MCIa to AD. The goal is to develop advanced diagnostic tools that support early and targeted interventions.

Exploring the Predicting Biomarkers From Mild Cognitive Impairment to Dementia (EBMID)

Mild cognitive impairment (MCI) represents a transitional stage between healthy aging and dementia, and affects more than 15% of the population over the age of 60 in China. About 15% patients with MCI could progress into dementia after two years and about one-third develop into dementia within five years, which will lead to suffering, as well as staggering economic and care burden. So, exploring the predicting biomarkers from MCI to dementia to identify and delay progression to dementia at an early stage is of great social and clinical significance. Some reports based on a single neural biomarker suggest that risk models can predict the conversion of MCI to dementia, but no widely recognized prediction models basing on multiple complex markers have been used in clinical practice. The objectives of this study are to outline the spectrum of MCI transforming into dementia through a 5-year prospective longitudinal cohort study; Secondly, screening biomarkers for MCI transmit to dementia are based on clinical symptoms, neuropsychology, neuroimaging, neuroelectrophysiology, and humoral markers tests data.