Clinical Risk Assessment and Prediction in Congenital Heart Disease Across the Lifespan: JACC Scientific Statement

Area of Science:

• Cardiology
• Medical Science

Background:

• Congenital heart disease (CHD) encompasses diverse structural anomalies with unique natural histories and long-term outcomes.
• Current risk prediction models for CHD face challenges in generalizability, validation, and long-term applicability.
• Risk assessment in CHD is complicated by numerous evolving factors throughout a patient's life.

Purpose of the Study:

• To address the challenges in lifelong risk measurement for congenital heart disease.
• To appraise existing and novel risk assessment frameworks for CHD.
• To identify domains of risk specific to CHD across the lifespan.

Main Methods:

• Review and appraisal of current and emerging risk measurement frameworks for CHD.
• Analysis of factors influencing adverse outcomes in CHD, including age, sex, genetics, and comorbidities.
• Examination of the need for large, longitudinal, prospective CHD cohorts with multidimensional data.

Main Results:

• Risk of adverse outcomes in CHD is dynamic and influenced by a multitude of evolving factors.
• Existing prediction models have limitations in predicting long-term risks.
• Emerging technologies offer potential for improved risk assessment, but require validation.

Conclusions:

• Accurate, lifelong risk assessment in CHD is crucial but challenging.
• There is a need for robust, longitudinal data and standardized methodologies for CHD risk stratification.
• Effective communication of risk to patients and families is essential and requires best practices.