Developing Digital Tools to Predict Alzheimers Disease and Dementia Risk Using Risk Factor Analysis with a Mobile Monitoring App

What this Trial Is About

Population aging is a major factor increasing the global prevalence of dementia. This research aims to identify and estimate risks linked to developing Alzheimers disease and other dementias by studying modifiable and non-modifiable factors. The study uses artificial intelligence algorithms to create a predictive tool and offers technological aids like an app for patient monitoring and a web platform for clinicians to improve risk assessment and personalized care. The trial has two phases a retrospective phase to build a predictive model for dementia risk and biological changes consistent with Alzheimers disease, and a prospective phase to validate this model. The intervention involves a mobile app designed to support remote health monitoring and patient engagement through gamification. Participants enter clinical data every three months, such as weight, blood pressure, and glucose levels. The app provides a qualitative risk assessment to aid clinical monitoring but does not replace medical evaluation. Participants will be involved by regularly inputting clinical variables into the app, which helps monitor their condition and engagement. Researchers will measure the rate of conversion to dementia from enrollment to three to six months later. The study does not involve other treatments. The total participation time corresponds to the monitoring period until the primary outcome is assessed. Safety monitoring and long-term follow-up details are not specified.

Digital Solutions for Predicting the Biological Mechanisms of Alzheimer's Disease Through the Analysis of Risk Factors