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Updated: Jun 24, 2026
Calcification of Vascular Smooth Muscle Cells and Imaging of Aortic Calcification and Inflammation
Published on: May 31, 2016
Machine learning derived abdominal aortic calcification is associated with physical frailty in community-dwelling
Abadi K Gebre1, Marion Mundt2,3, Elsa Dent4
1Nutrition & Health Innovation Research Institute, School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia.
Insights
Subclinical cardiovascular disease, measured as abdominal aortic calcification (AAC), is linked to physical frailty. Early detection of frailty may be possible using AAC from routine bone density scans.
Area of Science:
- Gerontology
- Cardiovascular Disease
- Biomedical Imaging
Background:
- Clinical cardiovascular disease (CVD) is common in frail individuals.
- The association between subclinical CVD markers like abdominal aortic calcification (AAC) and frailty is not well understood.
- Frailty is a significant geriatric syndrome associated with adverse health outcomes.
Purpose of the Study:
- To investigate the cross-sectional relationship between abdominal aortic calcification (AAC) and physical frailty.
- To assess if a machine learning model for AAC (ML-AAC24) can identify individuals at higher risk of frailty.
- To explore the potential of AAC as an early marker for frailty detection.
Main Methods:
- Utilized data from 49,081 participants in the UK Biobank Imaging Study without a prior atherosclerotic CVD diagnosis.
- Quantified abdominal aortic calcification (AAC) using a validated machine learning model (ML-AAC24) and categorized it into low, moderate, and high severity.
- Assessed physical frailty using a modified Fried's phenotype, including grip strength, walking speed, weight loss, exhaustion, and physical inactivity.
- Employed multivariable-adjusted multinomial logistic regression to analyze associations between ML-AAC24 extent and frailty status (pre-frail, frail).
Main Results:
- Approximately 20% of participants exhibited moderate or high levels of ML-AAC24.
- Individuals with moderate and high ML-AAC24 showed significantly greater odds of being pre-frail (ORs 1.06-1.14) and frail (ORs 1.27-1.58) compared to those with low ML-AAC24.
- Associations between ML-AAC24 and frailty status remained significant after adjusting for multiple covariates.
- Similar associations were observed when stratified by sex.
Conclusions:
- Higher degrees of abdominal aortic calcification (AAC), as assessed by ML-AAC24, are significantly associated with increased odds of physical frailty.
- AAC, detectable from lateral spine images during routine bone density testing, may serve as a valuable, non-invasive biomarker for early frailty detection.
- These findings underscore the importance of considering subclinical CVD markers in comprehensive geriatric care and frailty assessment.
Abstract:
Clinical cardiovascular disease (CVD) is often present in frail individuals. However, it remains unclear whether subclinical CVD, e.g., abdominal aortic calcification (AAC), is associated with frailty. This study investigated the cross-sectional relationship between AAC scored using a validated machine learning model (ML-AAC24) and physical frailty. 49,081 participants from the UK Biobank Imaging Study without atherosclerotic CVD (ASCVD) diagnosis were included. ML-AAC24 extent was categorised as low, moderate and high, based on established severity categories. Physical frailty was based on a modified Fried's frailty phenotype comprising weak hand grip strength, slow walking speed, weight loss, exhaustion, and physical inactivity. Individuals with three or more deficits were considered frail, while one or two deficits was considered pre-frail. Multivariable-adjusted multinominal logistic regression models were used to test the associations between ML-AAC24 extent and frailty status. One in five individuals had moderate or high ML-AAC24. Compared to individuals with low ML-AAC24, those with moderate and high ML-AAC24 had greater odds of being pre-frail (ORs 1.06 95%CI 1.00-1.12 moderate; 1.14 95%CI 1.04-1.26 high) or frail (ORs 1.27 95%CI 1.12-1.44 moderate; 1.58 95%CI 1.31-1.91 high), adjusted for multiple covariates. When stratified by sex, similar results for frailty were recorded. In a population, those with moderate and high ML-AAC24 were more likely to present as pre-frail and frail. AAC identified from lateral spine images obtained during routine bone density testing, could serve as a useful marker for the early detection of frailty, highlighting the importance of multimodality care.
