Related Experiment Video
Updated: Jun 21, 2025
Coronary Progenitor Cells and Soluble Biomarkers in Cardiovascular Prognosis after Coronary Angioplasty
Published on: January 28, 2020
Machine Learning-Based Prediction of In-Stent Restenosis Risk Using Systemic Inflammation Aggregation Index Following
Ling Hou1, Jinbo Zhao2, Ting He2
1Department of Central Hospital of Tujia and Miao Autonomous Prefecture, Hubei University of Medicine, Shiyan, Hubei Province, People's Republic of China.
Insights
The systemic inflammation aggregation index (AISI) is a significant predictor of in-stent restenosis (ISR) after drug-eluting stent implantation. Higher AISI levels indicate an increased risk of ISR development, aiding in patient risk assessment.
Area of Science:
- Cardiology
- Biomedical Engineering
- Medical Informatics
Background:
- Coronary artery disease (CAD) necessitates percutaneous coronary intervention (PCI), often with drug-eluting stents (DES).
- In-stent restenosis (ISR) remains a complication post-PCI, influenced by inflammation and platelet activation.
- The systemic inflammation aggregation index (AISI) shows potential for predicting adverse outcomes but lacks study in ISR.
Purpose of the Study:
- To investigate the utility of the systemic inflammation aggregation index (AISI) in predicting in-stent restenosis (ISR) after DES implantation.
- To identify key predictors of ISR using machine learning models.
Main Methods:
- Retrospective observational study of 1712 patients post-DES implantation.
- Evaluation of AISI, demographics, clinical history, and laboratory parameters using machine learning (Random Forest, XGBoost, etc.).
- Variable importance and SHAP analysis to interpret model predictions.
Main Results:
- In-stent restenosis (ISR) occurred in 25.8% of patients.
- The Random Forest model demonstrated high predictive accuracy for ISR (AUC 0.9569, accuracy 0.911).
- AISI was a prominent predictor, with higher values positively correlating with ISR risk.
Conclusions:
- The systemic inflammation aggregation index (AISI) is an independent risk factor for ISR post-DES.
- Elevated AISI levels signify a heightened probability of developing ISR.
- AISI can serve as a valuable tool for assessing ISR risk in patients undergoing DES implantation.
Introduction:
Coronary artery disease (CAD) remains a significant global health challenge, with percutaneous coronary intervention (PCI) being a primary revascularization method. In-stent restenosis (ISR) post-PCI, although reduced, continues to impact patient outcomes. Inflammation and platelet activation play key roles in ISR development, emphasizing the need for accurate risk assessment tools. The systemic inflammation aggregation index (AISI) has shown promise in predicting adverse outcomes in various conditions but has not been studied in relation to ISR.
Methods:
A retrospective observational study included 1712 patients post-drug-eluting stent (DES) implantation. Data collected encompassed demographics, medical history, medication use, laboratory parameters, and angiographic details. AISI, calculated from specific blood cell counts, was evaluated alongside other variables using machine learning models, including random forest, Xgboost, elastic networks, logistic regression, and multilayer perceptron. The optimal model was selected based on performance metrics and further interpreted using variable importance analysis and the SHAP method.
Results:
Our study revealed that ISR occurred in 25.8% of patients, with a range of demographic and clinical factors influencing the risk of its development. The random forest model emerged as the most adept in predicting ISR, and AISI featured prominently among the top variables affecting ISR prediction. Notably, higher AISI values were positively correlated with an elevated probability of ISR occurrence. Comparative evaluation and visual analysis of model performance, the random forest model demonstrates high reliability in predicting ISR, with specific metrics including an AUC of 0.9569, accuracy of 0.911, sensitivity of 0.855, PPV of 0.81, and NPV of 0.948.
Conclusion:
AISI demonstrated itself as a significant independent risk factor for ISR following DES implantation, with an escalation in AISI levels indicating a heightened risk of ISR occurrence.
