Dementia affects millions worldwide, with a significant impact in low- and middle-income countries like Kenya. However, current diagnostic tools are often unsuitable for African settings due to cultural, linguistic, educational, and economic differences compared to high-income countries. This creates an urgent need to adapt and validate diagnostic tools for accurate identification of dementia cases in Kenya.
The Brain and Mind Institute, in collaboration with the Davos Alzheimer’s Collaborative, is conducting a research study titled AD-DETECT-Kenya (Cultural Adaptation and Validation of Cognitive Tests, Functional Assessments and Biomarkers) in People with Dementia at the Aga Khan University Hospital in Nairobi. Led by primary investigators Drs. Karen Blackmon and Chinedu Udeh-Momoh, the study aims to discover, optimize, standardize, and validate measures and biomarkers specifically for dementia research in Kenya.
The study is designed as a non-interventional, cross-sectional, case-control investigation. It involves recruiting 200 participants: 40 with mild cognitive impairment (MCI), 80 with dementia, and 80 cognitively unimpaired individuals from Nairobi County. Participants will undergo various assessments during a single study visit, including interviews, questionnaires, cognitive tests, and bio-sample collection.
By comparing these groups and using statistical methods such as propensity score matching and machine learning, the study aims to identify the most effective diagnostic tools and markers for distinguishing between these three groups of participants. Ultimately, the findings will contribute to the development of a diagnostic toolkit tailored for use in Kenya. This toolkit will aid in accurately identifying dementia cases and serve as a resource for prevalence studies, risk reduction initiatives, and interventional research efforts related to dementia in the region.
The AD-DETECT-KENYA study addresses the specific challenges of dementia diagnosis in Kenya, aiming to improve understanding and management in low-resource settings.
Dementia affects millions worldwide, with a significant impact in low- and middle-income countries like Kenya. However, current diagnostic tools are often unsuitable for African settings due to cultural, linguistic, educational, and economic differences compared to high-income countries. This creates an urgent need to adapt and validate diagnostic tools for accurate identification of dementia cases in Kenya.
The Brain and Mind Institute, in collaboration with the Davos Alzheimer’s Collaborative, is conducting a research study titled AD-DETECT-Kenya (Cultural Adaptation and Validation of Cognitive Tests, Functional Assessments and Biomarkers) in People with Dementia at the Aga Khan University Hospital in Nairobi. Led by primary investigators Drs. Karen Blackmon and Chinedu Udeh-Momoh, the study aims to discover, optimize, standardize, and validate measures and biomarkers specifically for dementia research in Kenya.
The study is designed as a non-interventional, cross-sectional, case-control investigation. It involves recruiting 200 participants: 40 with mild cognitive impairment (MCI), 80 with dementia, and 80 cognitively unimpaired individuals from Nairobi County. Participants will undergo various assessments during a single study visit, including interviews, questionnaires, cognitive tests, and bio-sample collection.
By comparing these groups and using statistical methods such as propensity score matching and machine learning, the study aims to identify the most effective diagnostic tools and markers for distinguishing between these three groups of participants. Ultimately, the findings will contribute to the development of a diagnostic toolkit tailored for use in Kenya. This toolkit will aid in accurately identifying dementia cases and serve as a resource for prevalence studies, risk reduction initiatives, and interventional research efforts related to dementia in the region.
The AD-DETECT-KENYA study addresses the specific challenges of dementia diagnosis in Kenya, aiming to improve understanding and management in low-resource settings.
