- Finland researchers have developed a computational method capable of assessing the risk of sudden cardiac death from a one-minute heart rate measurement at rest.
- The new algorithm utilizes heart rate variability analysis to predict long-term risks of sudden cardiac death, with initial data showing significant predictive accuracy.
Physicists at Tampere University, Finland have developed a new computational method that can assess the risk of sudden cardiac death from a one-minute heart rate measurement at rest. This study was a collaborative effort between cardiology and computational physics disciplines.
Sudden cardiac arrest ranks among the top causes of death globally, nine out of 10 people who have a cardiac arrest outside of a hospital die — often within minutes.
Cardiac arrest occurs when the heart stops beating or beats so rapidly that it fails to pump blood effectively. This sudden event causes individuals to collapse and lose consciousness without any warning symptoms, hence earning the name “sudden cardiac arrest.”
To effectively plan preventive treatment, it is extremely important to be able to determine the risk of sudden cardiac arrest. Their study, JACC: Clinical Electrophysiology, highlights a new algorithm utilizing detrended fluctuation analysis (DFA2 a1). This metric is instrumental in detecting changes in heart rate variability, helping in the assessment of long-term risks associated with sudden cardiac death.
This method only requires one-minute measurements of heartbeat intervals at rest. The findings are based on data from stress tests conducted as part of their Finnish Cardiovascular Study (FINCAVAS) involving around 4,000 patients.
As per the study, patients identified with abnormal heart rate variability using this method experienced a notably higher rate of sudden death compared to those with normal heart rate patterns. The analysis also considered other risk factors in its assessment.
“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 research and development of this method are currently being expanded using various databases on different heart diseases. The goal is to identify not only the overall risk of sudden death but also common heart conditions like heart failure, which can be challenging to diagnose with existing healthcare methods. Initial results have shown great promise in achieving these objectives.
Edited by Harshajit Sarmah
