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Updated: Jun 6, 2025
12:18
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
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Risk Prediction Models for Mild Cognitive Impairment in Patients with Type 2 Diabetes Mellitus: A Systematic Review
Zhuoran Xia1,2, Songmei Cao1, Teng Li2
1Department of Nursing, Affiliated Hospital of Jiangsu University, Zhenjiang, 212001, People's Republic of China.
Diabetes, Metabolic Syndrome and Obesity : Targets and Therapy
|December 2, 2024
Summary
This review found that risk prediction models for mild cognitive impairment in type 2 diabetes patients show promise, with validated models achieving an AUC of 0.854. However, current models require improvement through rigorous, large-scale prospective studies.
Area of Science:
- Endocrinology
- Neurology
- Medical Informatics
Background:
- Type 2 diabetes mellitus is a growing global health concern.
- Mild cognitive impairment (MCI) is a common complication in patients with type 2 diabetes.
- Early identification of MCI risk in these patients is crucial for timely intervention.
Purpose of the Study:
- To systematically review and analyze existing risk prediction models for MCI in type 2 diabetes mellitus patients.
- To evaluate the predictive performance and identify key predictors within these models.
Main Methods:
- Comprehensive literature search across multiple databases (PubMed, Embase, Web of Science, etc.) up to November 2024.
- Systematic screening, data extraction, and risk of bias assessment using the Risk of Bias Assessment Tool for Prediction Models.
- Meta-analysis of predictive performance using Stata 17.0 software.
Main Results:
- 12 studies and 17 models were included, with Area Under the Curve (AUC) ranging from 0.743 to 0.987.
- All studies had a high risk of bias, particularly in data analysis reporting.
- Six validated models showed favorable predictive performance with a combined AUC of 0.854.
- Key predictors identified include age, education, disease duration, depression, and glycosylated hemoglobin.
Conclusions:
- Risk prediction models for MCI in type 2 diabetes are in early development.
- Current models demonstrate potential but require enhancement.
- Future research should focus on large-scale, multicenter prospective cohorts with rigorous study designs for improved accuracy and practicality.
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