Predicting Sudden Cardiac Death

Previously, the risk of sudden death has been assessed using parameters measured during a stress test. Researchers at Tampere University report developing a new computational method to estimate the risk of sudden death using a one-minute heart rate measurement while at rest based on data collected from the Finnish Cardiovascular Study (FINCAVAS) project from approximately 4,000 patients. They reported their findings from the interdisciplinary collaboration in JACC: Clinical Electrophysiology. 

The initial result appears to be promising. According to the researchers, making the assessment only requires heartbeat intervals measured during one minute at rest. Those with abnormal heart rate variability that were identified with the new method were found to have a significantly higher incidence of sudden cardiac death compared to those with normal heart rate characteristics. 

This method is not dependent on other measures and could be straightforwardly integrated into many applications such as a smart ring, or smartwatch giving it great potential for pre-diagnosis and identification of patients who may be at risk. Physicians could use the analysis to study the interdependencies of patient heart rate intervals and other complex properties characteristic of different heart diseases at different time scales.

"It is possible that in many previously asymptomatic individuals, who have suffered sudden cardiac death or who have been resuscitated after sudden cardiac arrest, the event would have been predictable and preventable if the emergence of risk factors had been detected in time," says Jussi Hernesniemi, Professor of Cardiology and lead author of the study.

"The most interesting finding of the study is the identification of differences specifically during measurements at rest. The characteristics of heart rate intervals of high-risk patients at rest resemble those of a healthy heart during physical exertion," says doctoral researcher Teemu Pukkila.

Currently, development and research of this method is being expanded with the assistance of various databases on different heart rates. The goal is to reliably identify the overall risk and most common heart diseases, such as heart failure which are laborious to diagnose using current methods.