About this trial
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.
Eligibility criteria
Qualifiers
Neuropsychological assessment possible (good level in French language, absence of visual/auditory deficit limiting the cognitive assessment)
Dementia with Lewy bodies according to the revised criteria of Mc Keith 2017 or probable AD defined according to McKhann 2011 criteria including CSF biomarkers (an abnormal level of beta-amyloid 1-42 protein [Ab42] or a pathological Ab42/Ab40 ratio and an abnormal level of phosphorylated tau [p-tau])
Neuropsychological assessment possible (good level in French language, absence of visual/auditory deficit limiting the cognitive assessment)
MMSE (Mini-mental State Examination) greater than or equal to 28, normal MemScreen test results, normal brain MRI and normal neurological examination
Disqualifiers
Contraindication to MRI
Other neurological or psychiatric or toxic/iatrogenic disorders that may account for the cognitive impairment or for EEG abnormalities
Any unstable medical pathology and/or that may account for the cognitive impairment
Trial design
Treatments tested in this trial
- EEG
Treatment groups
Sponsors and collaborators
Assistance Publique - Hôpitaux de Paris
Lead sponsor
Association des Aidants et Malades à Corps de Lewy (A2MCL)
Collaborator