Related Experiment Video
Updated: Jul 2, 2026
12:09
Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Published on: January 8, 2013
Electrocardiogram derived heart age models agreement, accuracy and predictive ability in the Tromsø study
Arya Panthalanickal Vijayakumar1, Tom Wilsgaard2, Henrik Schirmer3,4
1Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway. arya.p.vijayakumar@uit.no.
Npj Aging
|March 21, 2026
Summary
Convolutional neural networks (CNNs) accurately estimate heart age from electrocardiograms (ECGs). These CNNs show consistent prognostic value for cardiovascular events and mortality, regardless of architectural differences.
Area of Science:
- Cardiology
- Artificial Intelligence
- Biomedical Engineering
Background:
- Convolutional neural networks (CNNs) show potential for estimating heart age using electrocardiogram (ECG) data.
- Previous studies have developed various CNN models for ECG-based heart age estimation.
Purpose of the Study:
- To compare the accuracy, agreement, and prognostic value of three published CNN models for ECG-based heart age estimation.
- To evaluate the performance of these models in an independent cohort.
Main Methods:
- The Tromsø Study cohort, comprising 7,108 participants, was used for validation.
- Three distinct CNN architectures were assessed for their ability to predict chronological age from ECGs.
- Cox proportional hazards models and C-index were employed to evaluate the prognostic value of the estimated heart age (δ-age) for adverse cardiovascular outcomes and mortality.
Main Results:
- Mean absolute errors in age estimation ranged from 6.4 to 7.8 years across the CNN models.
- Correlations with chronological age were approximately 0.71-0.73, with high inter-model agreement (ICC 0.86).
- An elevated ECG-based heart age (δ-age) was significantly associated with increased risk for myocardial infarction, stroke, cardiovascular mortality, and all-cause mortality, with varying strengths for different models.
Conclusions:
- CNNs provide consistent ECG-based heart age estimations and comparable risk prediction capabilities, even with differing architectures and training datasets.
- ECG-derived heart age serves as a valuable prognostic marker for cardiovascular diseases and overall mortality.
Related Concept Videos
01:29Electrocardiogram
An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and the T...
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and the T...
01:25Correlation between ECG and Cardiac Cycle
The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...