New Research Suggests ECG Tests Could Predict Cognitive Decline

A groundbreaking preliminary study presented at the American Stroke Association’s International Stroke Conference 2025 suggests that electrocardiogram (ECG) tests, enhanced by artificial intelligence (AI) models, may predict premature aging and cognitive decline. This finding represents a significant step forward in understanding the intricate relationship between heart health and mental acuity.

Understanding ECG-Age

Unlike chronological age, ECG-age reflects the functional status of the heart, offering a deeper insight into overall health at a tissue level. Bernard Ofosuhene, B.A., the lead author and a clinical research coordinator at UMass Chan Medical School, explains: “ECG-age is a measure that captures the heart’s functional age, providing a more nuanced view of aging compared to simple calendar years.”

Existing Research on ECG-Age

Prior studies have demonstrated that ECG-age can accurately predict heart disease and mortality. This new research extends this understanding by exploring ECG-age’s potential link to cognitive impairment for the first time. Researchers delved into a dataset of over 63,000 participants from the UK Biobank, analyzing how ECG-age correlated with cognitive performance.

Methodology and Data Analysis

The participants, aged between 43 and 85, were evaluated using a comprehensive set of cognitive tests. AI was employed to determine each participant’s ECG-age, ensuring that cognitive data aligned with the timing of ECG testing. The dataset was divided into three groups based on their ECG-age: normal, accelerated, and decelerated.

Finding a Correlation

The analysis revealed a significant correlation between ECG-age and cognitive function:

• Participants whose ECG-age was younger than their actual age showed better performance on 6 out of 8 cognitive tests.
• Those with an ECG-age older than their chronological age exhibited worse performance on 6 of the same tests.

This suggests that a younger ECG-age may be indicative of better overall health and cognitive resilience.

Implications for Healthcare

Ofosuhene advocates for the wider adoption of ECG data analysis in healthcare settings. “ECG data is widely available in stroke treatment and can be leveraged to identify early signs of cognitive decline. Early diagnosis can lead to timely interventions, improving patient outcomes.”

Fernando D. Testai, M.D., Ph.D., a neurology professor at the University of Illinois College of Medicine, underscores the study’s importance: “This research highlights the heart-brain connection and suggests that ECG data analyzed by AI could provide a quicker and more objective assessment of cognitive function compared to traditional methods.”

Study Limitations and Future Directions

The study does have limitations. The sample included primarily individuals of European ancestry, aged 43 to 85, raising questions about the generalizability to other populations and age groups. Future research will aim to explore the impact of gender and diverse ancestry on the relationship between ECG-age and cognitive performance.

Additionally, determining whether ECG-age can predict future cognitive decline remains a critical question. Answering this could revolutionize predictive healthcare, potentially leading to new treatments that address heart-related cognitive impairments.

Conclusion

The study presents a promising link between ECG data and cognitive health, leveraging AI to interpret ECG findings. While further research is needed to confirm and expand these findings, early results suggest a powerful potential for ECG tests in detecting cognitive decline.

Healthcare professionals may soon find a valuable tool in their arsenal for assessing cognitive health, enabling early interventions and improved patient care.

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