The "Five Risks algorithm": an easy tool for cardiovascular risk estimation

Area of Science:

• Cardiology
• Preventive Medicine
• Public Health

Background:

• Cardiovascular disease remains a leading cause of mortality globally.
• Accurate risk stratification is crucial for timely intervention and treatment initiation.
• Current risk assessment tools may require simplification for broader clinical application.

Purpose of the Study:

• To develop and validate a straightforward tool for identifying individuals at high cardiovascular risk.
• To assess the utility of novel risk algorithms in guiding lipid-lowering treatment decisions.
• To compare the performance of new algorithms against established risk scores.

Main Methods:

• Development of the Five Risk (5R) algorithm incorporating male gender, high systolic blood pressure, high total cholesterol, smoking, and high blood sugar.
• Evaluation of the 5R algorithm's performance using Kappa coefficient against the Framingham Risk Score.
• Development and comparison of the Six Risk algorithm (6RDF) against the SCORE, considering diabetes and family history as exclusion criteria for treatment.

Main Results:

• The 5R algorithm identifies patients with three independent risk factors as candidates for lipid-lowering treatment.
• The 5R algorithm demonstrated a Kappa coefficient of 0.62 when compared to the Framingham Risk Score.
• The 6RDF algorithm achieved a Kappa coefficient of 0.70 when compared to the SCORE, with specific criteria for diabetes and family history.

Conclusions:

• The 5R algorithm offers a simplified approach to identifying patients requiring lipid-lowering therapy.
• The 6RDF algorithm provides a comparable or improved risk assessment over existing scores, particularly when considering specific patient subgroups.
• These novel algorithms can aid clinicians in making more efficient and effective cardiovascular risk management decisions.