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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Cognitive Impairment in Rural Elderly Population in Ecuador
Xavier Wong-Achi1, Gabriela Egas2, Dayana Cabrera3
1Ingapirca's Healthcare Center, Ingapirca, Cañar, Ecuador.
Introduction:
The Mini-Cog is a simple and short test that identifies cognitive impairment. Its detection helps provide an early dementia diagnosis, rapid access to treatments, and even delay or reversion.
Materials And Methods:
This multicenter, observational, descriptive, and cross-sectional study included 214 patients. Patients enrolled in this study were community dwellers aged ≥55-year-old, without prior diagnosis of cognitive impairment or dementia, with adequate hearing and vision functions. It was conducted in primary care health centers localized in rural communities of Ecuador.
Results:
Ages ranged from 50 to 98 years and there was predominance of female gender: 66% versus 33%. The percentage of illiteracy was 26.4% (CI: 25.32-27.48), and 63% (CI: 62.1-63.94) of patients had complete primary educational level. The overall prevalence of cognitive impairment was 50.9% (95% CI: 48.5-53.3) and 47.2% (95% CI: 45.2-49.2) in patients with risk factors. We found several established risk factors associated with cognitive impairment onset, including social factors, physiological factors, and comorbidities.
Conclusion:
This is the first epidemiological research of CI in rural populations in this country using the Mini-Cog as a screening tool. Adopting public health measures for the prevention and control of those modifiable risk factors could reduce the prevalence of cognitive impairment and even its progression to dementia.
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