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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Development of risk prediction model for cognitive impairment in patients with coronary heart disease: A study
Qing Wang1,2, Shihan Xu1,2, Fenglan Liu3
1The Second Department of Geriatrics, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Insights
This study identifies predictors of mild cognitive impairment in elderly patients with coronary heart disease (CHD). Understanding these factors can help in early intervention for cognitive decline in CHD patients.
Area of Science:
- Cardiology
- Neurology
- Geriatrics
Background:
- Coronary heart disease (CHD) and cognitive impairment are significant health concerns in the elderly.
- Patients with CHD exhibit a higher incidence and faster decline in cognitive function.
- Limited evidence exists on vascular risk factors specifically within the CHD population.
Purpose of the Study:
- To investigate potential predictors of mild cognitive impairment (MCI) in elderly patients with CHD.
- To establish a predictive model for MCI in this patient group.
- To facilitate early intervention strategies for cognitive decline post-CHD.
Main Methods:
- A cross-sectional study involving 378 elderly CHD patients (≥65 years).
- Cognitive function assessed using the MoCA scale, categorizing participants into impairment and normal groups.
- Analysis included demographic data, disease characteristics, laboratory tests, metabolites, and lifestyle factors.
Main Results:
- Correlation analysis was performed to identify factors associated with MCI development.
- Logistic regression was used to develop a predictive model for MCI.
- Model performance was evaluated using calibration and decision curves and will be validated on a separate dataset.
Conclusions:
- The study aims to establish a novel predictive model for MCI in CHD patients.
- This model can aid in the early detection and intervention of cognitive impairment.
- Future research will involve prospective cohort studies for further validation.
Background:
Ischemic heart disease and degenerative encephalopathy are two main sources of disease burden for the global elderly population. Coronary heart disease (CHD) and cognitive impairment, as representative diseases, are prevalent and serious illnesses in the elderly. According to recent research, patients with CHD are more likely to experience cognitive impairment and their cognitive ability declines more quickly. Vascular risk factors have been associated with differences in cognitive performance in epidemiological studies, but evidence in patients with CHD is more limited. Inextricably linked between the heart and the brain. Considering the unique characteristics of recurrent cognitive impairment in patients with CHD, we will further study the related risk factors. We tried to investigate the potential predictors of cognitive impairment in patients with CHD through a prospective, cross-sectional study.
Methods:
The cross-sectional study design will recruit 378 patients with CHD (≥65 years) from Xiyuan Hospital of China Academy of Chinese Medical Sciences. The subjects' cognitive function is evaluated with MoCA scale, and they are divided into cognitive impairment group and normal cognitive function group according to the score results. Demographic data, disease characteristics (results of coronary CT/ angiography, number of stents implanted, status of diseased vessels), laboratory tests (biochemistry, coagulation, serum iron levels, pulse wave velocity), metabolites (blood samples and intestinal metabolites), and lifestyle (smoking, alcohol consumption, sleep, physical activity) will be assessed as outcome indicators. Compare the two groups and the correlation analysis will be performed on the development of mild cognitive impairment. Mann-Whitney U or X2 test was selected to describe and evaluate the variation, and logistics regression analysis was employed to fit the prediction model. After that, do the calibration curve and decision curve to evaluate the model. The prediction model will be validated by a validation set.
Discussion:
To explore the risk factors related to mild cognitive impairment (MCI) in patients with CHD, a new predictive model is established, which can achieve advanced intervention in the occurrence of MCI after CHD. Owing to its cross-sectional study design, the study has some limitations, but it will be further studied by increasing the observation period, adding follow-up data collection or prospective cohort study. The study has been registered with the China Clinical Trials Registry (ChiCTR2200063255) to conduct clinical trials.
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