In a groundbreaking study presented at the EHRA 2025 scientific congress, researchers revealed how artificial intelligence (AI) is being harnessed to determine the heart's biological age through standard electrocardiograms (ECGs). This innovative technology has the potential to predict not just individual heart health but also the risk of mortality and major cardiovascular events.

Understanding Heart Age: The Concept of Biological and Chronological Ages

While a person’s heart has a chronological age that aligns with their date of birth, it also possesses a biological age that reflects its functional state. For instance, a 50-year-old individual with poor cardiovascular health may exhibit a biological heart age of 60, whereas another 50-year-old with excellent heart health might show a biological heart age of 40. This disparity suggests that heart health can significantly differ among individuals of the same chronological age.

By analyzing comprehensive data from approximately 500,000 12-lead ECGs, the research team developed a predictive algorithm focused on calculating biological heart age. The findings suggested that a biological heart age that surpasses chronological age by just seven years correlates with a staggering 62% increase in all-cause mortality risk and nearly double the risk of major adverse cardiovascular events (MACE).

AI's Role in Cardiac Risk Assessment

“Utilizing AI to assess biological heart age introduces a transformative shift in how we approach cardiovascular risk evaluation,” explained Associate Professor Yong-Soo Baek from Inha University Hospital in South Korea. The study utilized a deep learning-based algorithm trained on an extensive dataset collected over fifteen years, with a subsequent validation involving an independent cohort. The results were clear: biological heart age predicted mortality and cardiovascular outcomes far more effectively than chronological age alone.

The deep neural network was able to not only analyze the ECG data but also gauge cardiac function variations such as ejection fraction—an important measure of the heart's pumping efficiency. Interestingly, patients with a reduced ejection fraction frequently displayed higher biological heart ages, coupled with longer QRS durations and corrected QT intervals, which further hint at underlying cardiovascular issues.

The Future of Cardiac Healthcare: Early Detection and Intervention

This research holds immense potential for early intervention strategies in cardiovascular healthcare. With the ability to identify patients with higher biological heart ages, clinicians could target them for intensive lifestyle modifications and medical interventions. This novel approach may lead to significant improvements in patient outcomes.

“The correlation between biological heart age and increased cardiovascular risks emphasizes the potential of AI in enhancing early detection and proactive healthcare,” concluded Associate Professor Baek. “Our findings highlight the need for larger sample sizes in future studies to strengthen these conclusions and broaden the applicability of AI in clinical settings.”

As we advance in the integration of AI in healthcare, the implications for cardiovascular disease prevention could be monumental, potentially saving countless lives through earlier and more accurate risk assessments.

Stay tuned for what this innovative technology could mean for your heart health and the future of cardiology!