Related Experiment Video
Updated: Apr 7, 2026
Coronary Progenitor Cells and Soluble Biomarkers in Cardiovascular Prognosis after Coronary Angioplasty
Published on: January 28, 2020
Risk Factors of Coronary Artery Disease in Secondary Prevention--Results from the AtheroGene--Study
Elvin Zengin1, Christoph Bickel2, Renate B Schnabel1
1Department of General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany.
Insights
Diabetes mellitus is the strongest predictor of secondary cardiovascular events in patients with coronary artery disease (CAD). Combining traditional risk factors with clinical variables significantly improves risk stratification for better patient outcomes.
Area of Science:
- Cardiovascular Medicine
- Clinical Risk Stratification
- Predictive Analytics in Healthcare
Background:
- Cardiovascular (CV) risk factors are crucial for patient risk stratification.
- Traditional risk factors include diabetes mellitus, dyslipidemia (LDL/HDL ratio), hypertension, and smoking.
- Identifying predictors for secondary CV events is vital in managing patients with known coronary artery disease (CAD).
Purpose of the Study:
- To compare the predictive power of traditional CV risk factors versus clinical variables for secondary CV events.
- To evaluate the combined utility of traditional risk factors and clinical variables in risk stratification.
- To identify key predictors of cardiovascular death or non-fatal myocardial infarction in patients with established CAD.
Main Methods:
- Analysis of 3229 patients with known coronary artery disease (CAD).
- Assessment of traditional risk factors (diabetes, LDL/HDL ratio, hypertension, smoking) and clinical variables (ejection fraction, creatinine clearance, multi-vessel disease, CRP).
- Statistical analysis using hazard ratios (HR) and confidence intervals (CI) to determine prediction of secondary CV events over a mean follow-up of 4.2 years.
Main Results:
- Diabetes mellitus demonstrated the strongest influence on secondary events (HR: 1.70).
- Clinical variables like ejection fraction (HR: 3.30) and creatinine clearance (HR: 2.26) significantly improved risk prediction.
- The most precise risk prediction was achieved by combining all assessed clinical variables with traditional CV risk factors.
Conclusions:
- Diabetes mellitus is the most influential traditional risk factor for secondary CV events in CAD patients.
- Integrating clinical variables with traditional risk factors substantially enhances risk stratification accuracy.
- Effective control of CV risk factors, augmented by clinical variable assessment, is paramount for managing patients with known CAD.
Background:
Risk factors are important in cardiovascular (CV) medicine for risk stratification of patients. We aimed to compare the traditional risk factors to clinical variables for the prediction of secondary cardiovascular events.
Methods And Results:
For this study, 3229 patients with known coronary artery disease (CAD) were included. We calculated whether the traditional risk factors, diabetes mellitus, increased LDL/HDL ratio, arterial hypertension and smoking alone and in combination with the clinical variables, ejection fraction, creatinine clearance, multi-vessel disease and CRP concentration predict the outcome cardiovascular death or non-fatal myocardial infarction (N = 432) during the mean follow-up time of 4.2 ± 2.0 years. In this cohort diabetes mellitus was the risk factor with the strongest influence regarding occurrence of secondary events (hazard ratio; HR:1.70, confidence interval; CI 95%: 1.36-2.11; P<0.0001), followed by LDL/HDL ratio and smoking. However, risk stratification is further improved by using additional clinical variables like ejection fraction (HR:3.30 CI 95%:2.51-4.33; P>0.0001) or calculated creatinine clearence (Cockroft-Gault formula) (HR:2.26 CI 95%:1.78-2.89; P<0.0001). Further ameliorating risk stratification from the clinical variables were CRP and multi-vessel disease. The most precise risk prediction was achieved when all clinical variables were added to the CV risk factors.
Conclusion:
Diabetes mellitus has the strongest influence to predict secondary cardiovascular events in patients with known CAD. Risk stratification can further be improved by adding CV risk factors and clinical variables together. Control of risk factors is of paramount importance in patients with known CAD, while clinical variables can further enhance prediction of events.
Related Concept Videos
01:30Coronary Artery Disease I: Introduction
01:26Coronary Artery Disease IV: Preventive Measures
01:26Coronary Artery Disease II: Pathophysiology
01:26Atherosclerosis III: Management
01:27Atherosclerosis II: Clinical Manifestations and Diagnostic Tests
01:30Atherosclerosis I: Introduction