Heart failure risk prediction in the Multi-Ethnic Study of Atherosclerosis

Area of Science:

• Cardiology
• Preventive Medicine
• Epidemiology

Background:

• Heart failure (HF) is a significant cause of mortality, particularly in aging populations.
• Early identification of individuals at high risk for HF is crucial for effective primary prevention strategies.
• Existing risk assessment tools may not fully capture risk in individuals without diagnosed cardiac conditions.

Purpose of the Study:

• To develop and validate a predictive model for incident heart failure (HF) risk.
• To identify key risk factors for HF development in a population initially free of clinical cardiovascular disease.
• To create a practical risk score applicable in primary care settings.

Main Methods:

• Utilized data from the Multi-Ethnic Study of Atherosclerosis (MESA) cohort study.
• Included 6814 participants without baseline cardiovascular disease, followed for a median of 4.7 years.
• Employed Cox proportional hazards models to identify independent risk factors and generate a 5-year HF risk score, validated through bootstrapping.

Main Results:

• Identified significant independent predictors of HF: age, male gender, current smoking, body mass index, systolic blood pressure, heart rate, diabetes, N-terminal pro-B-type natriuretic peptide (NT-proBNP), and left ventricular mass index.
• A parsimonious model incorporating age, gender, BMI, smoking, SBP, heart rate, diabetes, and NT-proBNP achieved a high predictive accuracy (c-statistic of 0.87).
• The model effectively predicted incident HF risk over a 5-year period.

Conclusions:

• A clinical algorithm utilizing common primary care data can effectively identify individuals at high risk of developing heart failure.
• This risk assessment tool is valuable for proactive HF prevention in individuals without pre-existing cardiac disease.
• The developed model offers a practical approach for early HF risk stratification in routine clinical practice.