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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

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

Published on: January 11, 2020

Mild cognitive impairment: believe it or not?

Ricardo F Allegri1, Frank B Glaser, Fernando E Taragano

  • 1Servicio de Neuropsicologia SIREN, y Unidad de Investigacion Rene Baron del Instituto Universitario CEMIC, Buenos Aires, Argentina. rallegri@cemic.edu.ar

International Review of Psychiatry (Abingdon, England)
|October 18, 2008
PubMed

Insights

Mild cognitive impairment (MCI) is a controversial transitional state before dementia. Further research is needed to establish MCI as a clinical diagnosis and target for Alzheimer's disease prevention therapies.

Area of Science:

  • Neurology
  • Gerontology
  • Cognitive Science

Background:

  • Mild cognitive impairment (MCI) is debated as a transitional state preceding dementia.
  • Current definitions and conversion rates of MCI remain controversial.
  • MCI is a focus for Alzheimer's disease (AD) natural history and prevention studies.

Purpose of the Study:

  • To evaluate MCI as an established medical diagnosis.
  • To assess MCI as a valid target for Alzheimer's prevention therapy.

Main Methods:

  • Review of existing literature and consensus conference findings on MCI.
  • Analysis of neuropsychological studies proposing a hippocampal memory profile for MCI.
  • Consideration of diagnostic criteria for MCI and prodromal AD.

Main Results:

  • Experts disagree on critical aspects of MCI, including its clinical utility.
  • A hippocampal memory profile is proposed for MCI as prodromal AD, requiring further validation.
  • Consensus on MCI diagnostic criteria remains elusive despite numerous conferences.

Conclusions:

  • MCI's status as a distinct clinical diagnosis and therapeutic target is uncertain.
  • Further research is essential to refine MCI diagnostic criteria.
  • Future Alzheimer's disease diagnosis will likely integrate neuropsychological, neuro-imaging, and CSF biomarkers in early, pre-dementia stages.

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