Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-24 @ 11:50 AM
Ignite Modification Date:
2025-12-24 @ 11:50 AM
NCT ID:
NCT06068361
Brief Summary:
Dementia with Lewy body disease (DLB) is the second leading cause of degenerative cognitive disorder after Alzheimer's disease (AD). Its variable clinical expression makes diagnosis difficult. To date, there is no validated DLB diagnostic biomarker, despite several biomarkers in development (EEG, MRI, biology).
Studies have shown that an improvement in diagnostic performance could be obtained by combining different modalities biomarkers using machine learning.
The aim of this research is to identify the best combination of multimodal biomarkers for the diagnosis of DLB (EEG, MRI, biology, cognitive scores), using a machine learning approach applied to a clinical cohort.
Detailed Description:
Study population: Observational prospective cohort study including over 24 months at the GHU AP-HP. Nord Lariboisière, Cognitive Neurology Center : 50 probable DLB patients, 50 AD patients, and 30 control subjects with subjective cognitive impairment but without any element in favor of neurodegenerative disorders. Total clinical dataset n= 130.
Act :
* 32-electrode EEG (resting state, passive auditory and active visual task).
* 4 dry electrode EEG cap simultaneously with the 32-electrode EEG
Expected results: Improved DLB diagnosis performance using a combination of multimodal biomarkers (EEG, cognitive scores, plasma, brain MRI).
Study:
NCT06068361
Study Brief:
Protocol Section:
NCT06068361