What type of study is this?

This is a Validation Study study.

December 8, 2025European Heart Journal - Cardiovascular Imaging0 citationsOpen Access

A streamlined CMR-derived machine-learning model for estimating cardiovascular biological age: development and validation in the UK-Biobank and Multi-Ethnic Study of Atherosclerosis

GAGianni Andreozzi EPEsther Puyol‐Antón AYAlistair A. Young

Key Points

To develop a machine learning model for estimating cardiovascular biological age and assess its prognostic value.
Developed HeartAge using gradient-boosting regression in 3,760 UK-Biobank participants
HeartAge-gap calculated as the difference between HeartAge and chronological age
Tested associations with cardiovascular conditions and outcomes in 31,784 UK-Biobank participants and 897 MESA participants using logistic and Cox regression
2,316 participants (7.3%) experienced composite cardiovascular outcomes over a median 5.5-year follow-up
HeartAge-gap associated with composite cardiovascular outcomes in males and females independently of other factors
In females, increased HeartAge-gap predicted all-cause mortality regardless of chronological age

Abstract

Abstract Aims Current models predicting cardiovascular biological age rely on radiomics or complex large feature sets including T1 and strain. We developed and validated a machine learning-based cardiovascular biological age estimate (HeartAge) using cardiovascular-magnetic-resonance (CMR) phenotypes and assessed the prognostic value of its deviation from chronological age (HeartAge-gap) for cardiovascular outcomes and mortality. Methods and Results HeartAge was developed using gradient-boosting regression in 3,760 healthy UK-Biobank participants based on readily extractable CMR phenotypes. HeartAge-gap was defined as the difference between HeartAge and chronological age. The association of HeartAge-gap with prevalent cardiovascular conditions and composite cardiovascular outcome or all-cause mortality was tested in 31,784 UK-Biobank participants (64±7 years; 16,640 females) and validated in 897 Multi-Ethnic Study of Atherosclerosis (MESA) participants (60±10 years; 472 females) using logistic and Cox regression, respectively. Over a median 5.5-year follow-up (IQR:4.7-7.1), 2,316 (7.3%) and 363 (1.1%) participants experienced the composite cardiovascular outcome and all-cause mortality, respectively. Each one-year increase in HeartAge-gap, was associated with the composite cardiovascular outcome in females (HR:1.022, 95%CI:1.001-1.044, P=0.048) and males (HR:1.017, 95%CI:1.002-1.033, P=0.027) independently of chronological age and confounders including, body-mass-index, ischaemic heart disease, diabetes, and hypertension. In females only, increased HeartAge-gap predicted all-cause mortality (HR:1.061, 95%CI:1.007-1.118, P=0.027), regardless of chronological age. In female MESA participants only, increased HeartAge-gap predicted the cardiovascular outcome (HR:1.113, 95%CI:1.025-1.210, P=0.011) independently of chronological age and other confounders. Conclusion A biologically older cardiovascular system was independently associated with adverse cardiovascular outcomes across both sexes. In females, advanced cardiovascular ageing also predicts all-cause mortality, irrespective of chronological age.

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