Publications by authors named "L Cleret de Langavant"
Objective: Huntington's disease (HD) is a neurodegenerative disorder characterized by progressive motor, cognitive, and psychiatric symptoms. Our aim here was to identify factors that can be modified to slow disease progression even before the first symptoms appear.
Methods: We included 2636 presymptomatic individuals (comparison with family controls) drawn from the prospective observational cohort Enroll-HD, with more than 35 CAG repeats and at least two assessments of disease progression measured with the composite Huntington's disease rating Scale (cUHDRS).
Article Synopsis
- A study used machine learning to analyze cognitive and functional data from over 15,000 participants aged 50+ across several waves of the Survey of Health, Ageing, and Retirement in Europe (SHARE) to identify transitions to probable dementia.* -
- Findings showed the algorithm detected more cases of probable dementia than self-reports, particularly among older adults, with a higher incidence in females and strong associations with various risk factors like low education and health issues.* -
- The research suggests that machine learning can effectively identify dementia risk in large population studies that do not have clinical diagnoses, highlighting the utility of such methods in understanding dementia-related outcomes.*
Background: Because of the genetic transmission of Huntington's disease (HD), informal caregivers (ICs, i.e., non-professional caregivers) might experience consecutive and/or concurrent caregiving roles to support several symptomatic relatives with HD over their life.
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