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Updated: Jul 25, 2026
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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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Nomogram for predicting mild cognitive impairment in Chinese elder CSVD patients based on Boruta algorithm.
Yanzi Huang1, Wendie Huang1, Xiaoming Ma2
1Department of Neurology, The Third Affiliated Hospital of Soochow University, Changzhou, China.
Frontiers in Aging Neuroscience
|February 18, 2025
Summary
This study developed a nomogram for early identification of post-stroke cognitive impairment (PSCI) and post-stroke cognitive impairment with dementia (PSCID) in stroke patients, addressing the increasing prevalence of cerebral small vessel disease (CSVD). The nomogram provides a user-friendly tool for clinical application.
Area of Science:
- Neurology
- Geriatrics
- Medical Informatics
Background:
- Cerebral small vessel disease (CSVD) is increasingly prevalent, particularly in the elderly.
- Improved detection techniques are leading to higher reported rates of CSVD.
- Cognitive decline trajectories vary among individuals with CSVD.
Purpose of the Study:
- To develop a nomogram for the early identification of post-stroke cognitive impairment (PSCI) and post-stroke cognitive impairment with dementia (PSCID).
- To create a clinically applicable tool for stroke patients at risk of cognitive decline.
Main Methods:
- Retrospective cohort study utilizing chained data imputation.
- Boruta algorithm for variable selection based on importance.
- Logistic regression with backward stepwise selection, visualized as a nomogram.
Main Results:
- The developed nomogram demonstrates clinical utility and user-friendliness.
- The nomogram passed the Hosmer-Lemeshow goodness-of-fit test.
- ROC and calibration curves confirmed high discriminative ability.
Conclusions:
- The nomogram integrates demographic and clinical indicators for medical application.
- Endocrine metabolic indicators, such as IGF-1, show early predictive value for cognitive decline.
- The study provides a succinct tool for managing CSVD-related cognitive issues.
