Automated abdominal aortic calcification scoring from vertebral fracture assessment images and fall-associated hospitalisations: the Manitoba Bone Mineral Density Registry

Le résumé fourni par la source

Abdominal aortic calcification (AAC), a subclinical measure of cardiovascular disease (CVD) that can be assessed on vertebral fracture assessment (VFA) images during osteoporosis screening, is reported to be a falls risk factor. A limitation to incorporating AAC clinically is that its scoring requires trained experts and is time-consuming. We examined if our machine learning (ML) algorithm for AAC (ML-AAC24) is associated with a higher fall-associated hospitalisation risk in the Manitoba Bone Mineral Density (BMD) Registry. A total of 8565 individuals (94.0% female, age 75.7 ± 6.8 years) who had a BMD and VFA image from DXA between February 2010 and December 2017 were included. ML-AAC24 was categorised based on established categories (ML-AAC24 = low < 2; moderate 2 to < 6; high ≥ 6). Cox proportional hazards models assessed the relationship between ML-AAC24 categories and incident fall-associated hospitalisations obtained from linked health records (mean ± SD follow-up, 3.9 ± 2.2 years). Individuals with moderate (9.6%) and high ML-AAC24 (11.7%) had a greater proportion of fall-associated hospitalisations, compared to those with low ML-AAC24 (6.0%). In age and sex-adjusted models, compared to low ML-AAC24, moderate (HR 1.49, 95% CI 1.24-1.79) and high ML-AAC24 (HR 1.89, 95% CI 1.56-2.28) were associated with greater hazards for a fall-associated hospitalisation. Results were comparable (HR 1.37, 95% CI 1.13-1.65 and HR 1.60, 95% CI 1.31-1.95, respectively) after multivariable adjustment, including prior falls and CVD, as well as medication use. Integrating ML-AAC24 into bone density machine software to identify high risk individuals would opportunistically provide important information on fall and cardiovascular disease risk to clinicians for evaluation and intervention.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.