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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

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Clinical Predictors for Mild Cognitive Impairment Progression in a Korean Cohort

Yong S Shim1, Dong Won Yang1, Bora Yoon2

  • 1Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul, Korea.

Dementia and Neurocognitive Disorders
|March 26, 2019
PubMed
Abstract

Insights

Predicting dementia progression from mild cognitive impairment (MCI) is crucial. Key clinical factors like age, APOE ε4, and cognitive test scores significantly predict progression, not medical expenses.

Area of Science:

  • Neuroscience
  • Gerontology
  • Clinical Neurology

Background:

  • Mild cognitive impairment (MCI) is a transitional stage between normal aging and dementia.
  • Patients and caregivers are concerned about the progression rate from MCI to dementia.
  • Identifying predictors of MCI progression is vital for timely intervention.

Purpose of the Study:

  • To identify clinical predictors of dementia progression in a Korean cohort of individuals with MCI.
  • To investigate the impact of frequently prescribed, evidence-lacking medications on MCI progression.
  • To analyze the relationship between medical expenses and MCI progression.

Main Methods:

  • A Korean cohort of older adults with MCI was analyzed.
  • Clinical characteristics and total medical expenses were compared between those who progressed to dementia and those who did not.
  • Cox proportional hazards regression analysis was employed to determine predictors.

Main Results:

  • Over a mean follow-up of 1.42 years, 27.63% of participants progressed to dementia.
  • Significant predictors included older age, apolipoprotein ε4 allele, higher Clinical Dementia Rating scale-sum of boxes, lower Instrumental Activities of Daily Living scores, and lower Mini-Mental State Examination scores.
  • Total medical expenses did not differ between the groups.

Conclusions:

  • The study confirms established clinical predictors for MCI to dementia progression.
  • Clinical factors, rather than medical expenses, are key indicators of progression.
  • Findings support the need for focused monitoring based on identified clinical predictors.
Keywords:
cholinesterase inhibitorsdementiamild cognitive impairmentpredictors

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