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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Advancing dementia preparedness in Low and Middle Income countries: A randomized trial to improve diagnosis in
Jorge J Llibre-Guerra1, Tania Zayas Llerena2, Zaily Martínez Figueroa2
1Department of Neurology, Washington University in Saint Louis School of Medicine, Saint Louis, Missouri, USA.
Introduction:
Dementia disproportionately affects individuals in low- and middle-income countries (LMICs), yet diagnostic capabilities there are often inadequate. This study assesses the impact of a structured training program for primary care physicians (PCPs) in Cuba to improve early dementia detection.
Methods:
We conducted a cluster-randomized trial involving 16 primary care clinics, randomizing them into intervention and control groups (CGs). The intervention group (IG) received comprehensive training on dementia diagnosis and management. The effectiveness was measured through changes in diagnosis rates and PCP diagnostic confidence over a 12-month period.
Results:
The IG demonstrated a significant improvement in PCP confidence and dementia diagnosis rates compared to baseline and the CG. Comparisons of clinic-based and community-based dementia prevalence highlighted the effectiveness of the intervention.
Discussion:
Structured training can significantly enhance the capabilities of PCPs in LMICs for early dementia detection. Ongoing training and integration into health systems are critical for sustaining these improvements.
Highlights:
This study developed and implemented a tailored training program for PCPs to specifically enhance their skills in dementia diagnosis. We used the 10/66 dementia protocol to benchmark and validate the effectiveness of the training program against community-based prevalence rates. In a cluster-randomized trial, we observed a significant post-training increase in dementia detection in primary care settings. Similar programs may address healthcare disparities by demonstrating the feasibility and impact of educational interventions in resource-constrained settings. We provide evidence-based recommendations for scaling similar training programs across other LMICs to improve dementia care globally.
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