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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Metabolic Syndrome and cognitive decline in the elderly: A systematic review
Naima Assuncao1,2, Felipe Kenji Sudo1,3, Claudia Drummond1,4
1Memory Clinic, D'Or Institute for Research and Education, Rio de Janeiro, Brazil.
Background:
Metabolic Syndrome (MetS) refers to a cluster of metabolic disturbances which is associated with increased risk for vascular and degenerative conditions in general population. Although the relationship between vascular risk factors and dementia is undisputable, additional hazard for cognitive decline in older population with concurrent metabolic disorders still waits to be demonstrated. The present review aims to analyze data on MetS and risk for cognitive decline in elderly persons.
Methods:
Database searches were performed in Medline, ISI and PsycINFO for articles assessing cognitive performances of older subjects with MetS.
Results:
Of a total of 505 studies, 25 were selected for the review. Risk of selection biases was identified in all the studies. Although all articles followed recognized diagnostic recommendations for MetS, minor criteria modifications were detected in most of them. Hyperglycemia was consistently associated with impaired cognitive performances in older individuals, but the role of MetS for cognitive decline and for the onset of dementia showed heterogeneous results.
Discussion:
Current available data in the literature concerning the impact of MetS on the cognition of older population is inconclusive and based on inconsistent evidence. Differential effects of individual MetS components and factors associated with the age of the sample may have accounted for divergent findings among articles, but larger and higher quality studies in this field are still needed.
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