First Model to Predict Sudden Cardiac Death

A sudden cardiac death (SCD) predictive model developed by the researchers from Emory's Rollins School of Public Health can help identify and prevent the disease in individuals at high risk.

With SCD affecting nearly 300,000 to 400,000 Americans annually, lead researcher Alvaro Alonso, MD, PhD, associate professor in the Department of Epidemiology at Rollins School of Public Health and his team developed the first predictive tool to assess the future risk of SCD among the general population. The team analyzed data from 18,000 adults without a prior history of cardiovascular disease.

‘In cardiac arrest, the heart abruptly stops beating. Without prompt intervention, it can result in the person's death. The main symptom is loss of consciousness and unresponsiveness.’

Findings suggest that information on age, sex and race along with traditional cardiovascular risk factors such as smoking, high blood pressure, diabetes and high cholesterol as well as specific SCD-related predictors and biomarkers can be leveraged to predict the risk of SCD.

"Not unexpectedly, we found that traditional risk factors associated with cardiovascular disease (smoking, diabetes, hypertension) predicted sudden cardiac death," explains Alonso. "However, we also found other predictors specific to sudden cardiac death, such as measures derived from the electrocardiogram and some blood biomarkers. African Americans had higher risk of sudden cardiac death than white individuals."



Source: Eurekalert