Cardiac risk
Pro Research Analysisby 
Searched over 200M research papers for "cardiac risk"
Consensus Meter
Understanding Cardiac Risk: Key Factors and Prediction Models
Introduction to Cardiac Risk Factors
Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality worldwide. Identifying and managing risk factors is crucial for preventing adverse cardiac events. Traditional risk factors such as hypertension, dyslipidemia, and smoking are well-established, but recent research has highlighted additional factors that may contribute to cardiovascular risk.
Traditional and Novel Risk Factors
Established Risk Factors
Traditional risk factors for cardiovascular disease include age, hypertension, dyslipidemia, smoking, and diabetes. These factors are the primary targets for therapeutic interventions aimed at reducing cardiovascular risk .
Emerging Risk Factors
Recent studies have identified several novel risk factors that may contribute to cardiovascular disease. These include left ventricular hypertrophy, hyperhomocysteinemia, elevated lipoprotein(a), hypertriglyceridemia, oxidative stress, and hyperfibrinogenemia. Understanding these new risk factors can provide insights into the mechanisms underlying cardiovascular disease and help in developing more comprehensive risk assessment models.
Cardiac Risk Prediction Models
Revised Cardiac Risk Index (RCRI)
The Revised Cardiac Risk Index (RCRI) is widely used to predict perioperative cardiac complications. It discriminates moderately well between patients at low and high risk for cardiac events after noncardiac surgery, with an area under the receiver-operating characteristic curve (AUC) of 0.75. However, its accuracy is lower for predicting cardiac events after vascular noncardiac surgery and for predicting death.
Framingham Risk Score (FRS)
The Framingham Risk Score (FRS) is a well-known model used to estimate the 10-year risk of coronary heart disease (CHD). It incorporates traditional risk factors and has been adapted for different populations, including the Japanese urban population through the Suita score. However, the absolute predicted risks from different models cannot be directly compared, and treatment decisions often depend on the specific model and its recommended risk threshold.
Other Prediction Models
A systematic review identified 363 prediction models for estimating cardiovascular risk in the general population, highlighting the proliferation of risk scores. Many of these models focus on atherosclerotic cardiovascular disease, with few addressing heart failure as an outcome. This gap suggests a need for models that can predict a broader range of cardiovascular outcomes, including heart failure.
Lifetime Risk and Long-Term Predictions
Lifetime Risk Assessment
Lifetime risk assessment provides a comprehensive view of an individual's risk of developing cardiovascular disease over their lifetime. Studies have shown that individuals with an optimal risk-factor profile have significantly lower lifetime risks of cardiovascular events compared to those with multiple major risk factors. This approach underscores the importance of maintaining a healthy risk-factor profile throughout life.
Long Working Hours and Cardiovascular Risk
Recent meta-analyses have linked long working hours (≥55 hours per week) with an increased risk of coronary heart disease and stroke. The evidence suggests a small but significant risk, although the mechanisms remain unclear and may involve stress-related, behavioral, or biological factors.
Conclusion
Effective cardiovascular risk assessment requires a combination of traditional and novel risk factors, along with robust prediction models. While established models like the RCRI and FRS provide valuable insights, there is a need for more comprehensive models that can predict a wider range of cardiovascular outcomes, including heart failure. Understanding and addressing both traditional and emerging risk factors can enhance the prevention and management of cardiovascular disease.
Sources and full results
Most relevant research papers on this topic