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Using Machine Learning to Evaluate the Role of Microinflammation in Cardiovascular Events in Patients With Chronic
Xiao Qi Liu1, Ting Ting Jiang1, Meng Ying Wang1
1Institute of Nephrology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.
Insights
Microinflammation, indicated by high hypersensitive C-reactive protein (hs-CRP), strongly predicts cardiovascular disease (CVD) events in chronic kidney disease (CKD) patients. Targeting microinflammation is crucial for preventing CVD in statin-treated CKD individuals.
Area of Science:
- Nephrology
- Cardiology
- Biochemistry
Background:
- Chronic kidney disease (CKD) patients frequently experience lipid metabolism disorders, increasing their risk of cardiovascular disease (CVD).
- Standard statin therapies offer limited efficacy in improving CVD outcomes for CKD patients.
- The impact of microinflammation on CVD development in CKD patients undergoing statin treatment requires further investigation.
Purpose of the Study:
- To investigate the influence of microinflammation on cardiovascular disease (CVD) risk in patients with chronic kidney disease (CKD) receiving statin therapy.
- To develop predictive models for low-density lipoprotein (LDL) levels and CVD indices using machine learning algorithms.
- To identify key predictors of CVD events in this patient cohort.
Main Methods:
- Retrospective analysis of statin-treated CKD patients from January 2013 to September 2020.
- Application of machine learning algorithms, including random forest (RF), for predictive modeling.
- Evaluation of model performance using fivefold cross-validation, accuracy, and area under the receiver operating characteristic (ROC) curve (AUC).
Main Results:
- The random forest (RF) algorithm demonstrated high accuracy for both low-density lipoprotein (LDL) and cardiovascular disease (CVD) models (82.27% and 74.15%, respectively).
- Hypersensitive C-reactive protein (hs-CRP) emerged as a highly relevant predictor in the LDL model and the strongest predictor of CVD events.
- Statin use and sex were found to have minimal impact on both LDL and CVD outcomes.
Conclusions:
- Microinflammation is significantly associated with the risk of cardiovascular disease (CVD) events in chronic kidney disease (CKD) patients.
- Therapeutic strategies targeting microinflammation are recommended for preventing CVD in CKD patients undergoing statin treatment.
- hs-CRP serves as a critical biomarker for assessing CVD risk in this population.
Background:
Lipid metabolism disorder, as one major complication in patients with chronic kidney disease (CKD), is tied to an increased risk for cardiovascular disease (CVD). Traditional lipid-lowering statins have been found to have limited benefit for the final CVD outcome of CKD patients. Therefore, the purpose of this study was to investigate the effect of microinflammation on CVD in statin-treated CKD patients.
Methods:
We retrospectively analysed statin-treated CKD patients from January 2013 to September 2020. Machine learning algorithms were employed to develop models of low-density lipoprotein (LDL) levels and CVD indices. A fivefold cross-validation method was employed against the problem of overfitting. The accuracy and area under the receiver operating characteristic (ROC) curve (AUC) were acquired for evaluation. The Gini impurity index of the predictors for the random forest (RF) model was ranked to perform an analysis of importance.
Results:
The RF algorithm performed best for both the LDL and CVD models, with accuracies of 82.27% and 74.15%, respectively, and is therefore the most suitable method for clinical data processing. The Gini impurity ranking of the LDL model revealed that hypersensitive C-reactive protein (hs-CRP) was highly relevant, whereas statin use and sex had the least important effects on the outcomes of both the LDL and CVD models. hs-CRP was the strongest predictor of CVD events.
Conclusion:
Microinflammation is closely associated with potential CVD events in CKD patients, suggesting that therapeutic strategies against microinflammation should be implemented to prevent CVD events in CKD patients treated by statin.
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