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Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025

Dementia Data Landscape 1. Cohorts.

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Morgan Amelia, Durkin Conor, Tari Benjamin, Squires Emma, Young Simon, Bauermeister Joshua, Bauermeister Sarah, Gallacher John

Аннотация

INTRODUCTION: Understanding and maximizing complex health data is crucial for accelerating discovery, translational research, funding priorities, and improving data management. Rapid, cost-effective progress can be made by repurposing datasets. This work explores the dementia cohort landscape, identifies cohorts relevant to dementia translation, and highlights areas to strengthen health cohort infrastructure.

METHOD: PubMed was searched for publications utilizing dementia-related cohorts (1970-2024), supplemented by international dementia data platforms. A template aligned with the C-Surv data model was used to summarize administrative details and the presence of measurements across 17 themes.

RESULTS: From 4596 publications and 11 data platforms, 883 cohorts were identified (558 population and 325 clinical). Of these, 74% indicated data availability for future research, though metadata reporting varied. Cohort metadata are accessible via the landscape tool.

DISCUSSION: This work reveals extensive global dementia-related data for repurposing and identifies priority areas for improvement, including metadata transparency, data accessibility, and locations to prioritize for future research.

HIGHLIGHTS: A total of 883 cohorts were identified globally (1970 to 2024): 558 population and 325 clinical The Global South is substantially underrepresented Seventy-four percent of cohorts offer data access, but protocols and metadata quality vary widely Only 45% of cohorts were discoverable via existing data platforms The online landscape tool enables strategic discovery and reuse of dementia data.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты