Early Detection of Alzheimer's Disease and Affective Disorders by Automated Voice and Speech Analysis (PLATA)

Recruiting

• Conditions: Neurocognitive Disorders
• Interventions: Other: Series of cognitive tasks during a semi-automated call

• Registration Number: NCT05943834
• Lead Sponsor: Centre Hospitalier Universitaire de Nice

Brief Summary

PLATA aims to develop an algorithm to identify vocal biomarkers of Alzheimer's dementia.

Using data collected as part of routine care, speech patterns will be compared to known biomarkers of Alzheimer's disease, such as amyloid 1-42 and p-Tau in CSF (cerebrospinal fluid).

If biomarkers of speech can be identified in Alzheimer's disease, it is possible that patients and research participants will no longer need to undergo need to undergo the intensive and invasive baseline biomarker methods currently used, such as lumbar punctures and PET scans.

Detailed Description

Not available

Study Timeline

• Status Verified: 2023-07
• Study First Submitted: 2023-07-05
• Study First Submitted QC: 2023-07-05
• Study Start: 2023-07-13
• Study First Posted: 2023-07-13
• Last Update Submitted: 2023-07-13
• Last Update Posted: 2023-07-14
• Primary Completion: 2024-07-13
• Study Completion: 2024-08-13

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 100

Inclusion Criteria

• Age ≥ 50 years
• Diagnosis relevant biomarker and neuropsychological data already available
• Cognitively healthy to very mild dementia (CDR score max. 0.5)
• Sufficient knowledge of the study language to understand study information, non opposition form,and questionnaires
• Expression of non opposition

Exclusion Criteria

• Hearing problems
• Patient protected by law, under guardianship or curator ship, or not able to participate in a clinical study according to the article L.1121-16 of the French Public Health Code

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Patients with a minor or major neurocognitive disorder	Series of cognitive tasks during a semi-automated call	Every patient will receive one semi-automated phone call, during the call a series of cognitive tasks will be performed. Each task will be recorded in a secondary audio stream which records the participant responses to allow for deep speech analysis of performance on these tasks

Primary Outcome Measures

Name	Time	Method
Build and validate speech-based machine learning models for relevant Phenotype detection through access to phenotyped patients from reference memory center.	20 minutes	Speech biomarker algorithm(s)

Trial Locations

Locations (1)

CHU de Nice; 🇫🇷 Nice, France