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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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Risk factors for predicting progression from normal cognition to mild cognitive impairment: protocol for a systematic

Jie Wang1, Lina Wang1, Xianglian Zhou1

  • 1School of Nursing, Huzhou University, Huzhou, Zhejiang, China.

BMJ Open
|June 14, 2019
PubMed
Abstract

Insights

This meta-analysis will identify risk factors for mild cognitive impairment (MCI), an early stage of Alzheimer's disease. By synthesizing existing research, we aim to clarify which factors predict cognitive decline, aiding early intervention strategies.

Area of Science:

  • Neurology
  • Gerontology
  • Public Health

Background:

  • Mild cognitive impairment (MCI) is a precursor to Alzheimer's disease, necessitating research into its risk factors.
  • Existing studies on MCI risk factors yield conflicting results, highlighting the need for a comprehensive review.
  • Understanding these risk factors is crucial for developing effective early detection and intervention strategies.

Purpose of the Study:

  • To conduct a systematic review and meta-analysis of cohort studies.
  • To identify and quantify risk factors associated with the progression from normal cognition to MCI.
  • To provide a consolidated evidence base for understanding cognitive disruption in MCI.

Main Methods:

  • A systematic search of seven electronic databases (MEDLINE, EMBASE, Cochrane Library, Web of Science, CNKI, Wan Fang, CBM) will be performed.
  • Two independent researchers will screen studies for eligibility and extract data using Newcastle Ottawa Scale (NOS) for quality assessment.
  • Disagreements will be resolved through consensus, with Stata V.15.1 used for analysis.

Main Results:

  • This section is to be populated upon completion of the meta-analysis.

Conclusions:

  • This meta-analysis will offer a clearer understanding of the risk factors predicting cognitive impairment.
  • Findings will inform clinical practice and public health initiatives aimed at mitigating MCI progression.
  • The results will be disseminated through peer-reviewed publication.
Keywords:
meta-analysismild cognitive impairmentnormal cognitionrisk factor

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