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Updated: Aug 26, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The complex burden of determining prevalence rates of mild cognitive impairment: A systematic review
Maria Casagrande1, Giulia Marselli2, Francesca Agostini2
1Department of Dynamic and Clinical Psychology and Health Studies, "Sapienza" University of Rome, Rome, Italy.
Abstract:
Mild cognitive impairment (MCI) is a syndrome characterized by a decline in cognitive performance greater than expected for an individual's age and education level, but that does not interfere much with daily life activities. Establishing the prevalence of MCI is very important for both clinical and research fields. In fact, in a certain percentage of cases, MCI represents a prodromal condition for the development of dementia. Accordingly, it is important to identify the characteristics of MCI that allow us to predict the development of dementia. Also, initial detection of cognitive decline can allow the early implementation of prevention programs aimed at counteracting or slowing it down. To this end, it is important to have a clear picture of the prevalence of MCI and, consequently, of the diagnostic criteria used. According to these issues, this systematic review aims to analyze MCI prevalence, exploring the methods for diagnosing MCI that determine its prevalence. The review process was conducted according to the PRISMA statement. Three thousand one hundred twenty-one international articles were screened, and sixty-six were retained. In these studies, which involved 157,035 subjects, the prevalence of MCI ranged from 1.2 to 87%. The review results showed a large heterogeneity among studies due to differences in the subjects' recruitment, the diagnostic criteria, the assessed cognitive domains, and other methodological aspects that account for a higher range of MCI prevalence. This large heterogeneity prevents drawing any firm conclusion about the prevalence of MCI.
Insights
Mild cognitive impairment (MCI) prevalence varies widely due to differing diagnostic methods and subject recruitment across studies. This significant heterogeneity prevents definitive conclusions on MCI prevalence rates.
Area of Science:
- Neurology
- Gerontology
- Epidemiology
Background:
- Mild cognitive impairment (MCI) signifies a cognitive decline beyond normal aging, potentially preceding dementia.
- Accurate MCI prevalence data is crucial for clinical practice, research, and early intervention strategies.
- Identifying MCI characteristics aids in predicting dementia development and implementing preventive measures.
Conclusions:
- The wide range of MCI prevalence highlights substantial methodological heterogeneity in existing research.
- Current data limitations prevent drawing firm conclusions on the precise prevalence of MCI.
- Further standardization in diagnostic criteria and methodology is needed for reliable MCI prevalence estimation.
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