MCI in LMICs Systematic Reviews and Model Development
Explore the latest updates on Mild Cognitive Impairment (MCI) in Low- and Middle-Income Countries (LMICs), including systematic reviews on prevalence and progression to dementia. Discover parameter estimates, secondary datasets for model development, and an output plan for four research papers in the field.
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MCI in LMICs Systematic Reviews MCI in LMICs Systematic Reviews Two reviews: 1. Systematic review on prevalence of MCI in LMICs - search updated to January 2019 N=39 (English and Spanish) + N=45 (Chinese articles, extracted by the group in Zheizang University) Results to be synthesised and discussion written 2. New protocol written for a systematic review investigating risk of progression from MCI to dementia in LMICs Preliminary search identified >10,000 articles Search terms currently being modified to better focus the electronic search Protocol to then be registered and paper prepared
10/66 Updated Results 10/66 Updated Results Parameter Estimates (whole sample only) Parameter Estimates (whole sample only) Study N C-statistics 95% CI CAIDE Original score 6,537 0.566 0.543 0.590 Updated score 6,537 0.713 0.693 0.732 AGECODE Original score 4,569 0.651 0.630 0.671 Updated score 11,104 0.746 0.732 0.761 BDSI Original score 8,360 0.675 0.654 0.696 Updated score 10,398 0.714 0.699 0.730 ANUADRI Original score 10,393 0.685 0.669 0.701 Updated score 10,394 0.716 0.701 0.732
Secondary Datasets for Model Development Secondary Datasets for Model Development Already Obtained Already Obtained The Mexican Health and Aging Study (MHAS) The Chinese Longitudinal Healthy Longevity Survey (CLHSLS) The Costa Rican Longevity and Healthy Aging Study (CRELES) The Indonesian Family Life Survey (IFLS)
Output Plan Four papers 1. SR Operationalisation strategies and MCI prevalence in LMICs 2. SR MCI and risk of dementia in LMICs 3. 10/66 dementia risk prediction model external validation and re- calibration 4. Dementia risk model development (in LMIC cohort studies from across the world) and validation (in the 10/66 dataset) NOTE: May want to publish results for each country separately depending on whether the models are similar across different sites
