Abdominal aortic calcification detected by dual X-ray absorptiometry: A strong predictor for cardiovascular events

Ann Med. 2010 Oct;42(7):539-45. doi: 10.3109/07853890.2010.515604.

Abstract

Background: Vertebral fracture assessment (VFA) using dual-energy X-ray absorptiometry can visualize abdominal aortic calcification (AAC). AAC correlates with total atherosclerosis burden. We questioned whether VFA-detected AAC could be used for cardiovascular risk assessment.

Methods: VFA images of 2,500 subjects were evaluated to detect and score AAC (n = 164). A random age- and gender-matched set of subjects (n = 325) without AAC served as control group. Patients with prior cardiovascular disease or procedures were excluded. Base-line cardiovascular risk factors and further cardiovascular events were checked. Design-based Cox regression analysis was used to examine the prognostic value of AAC for cardiovascular outcomes.

Results: AAC-positive subjects were divided into two groups: low-AAC (score 1–3), and high-AAC group (score > 3). Mean age in the groups was 68, 68, and 71 years, percentage of females was 64.4%, 61%, and 66.1%, and the proportion of cardiovascular events within groups was 1.5%, 6.7%, and 11.9% in control, low-AAC, and high-AAC groups, respectively. Age- and gender-adjusted as well as multivariable analysis showed a significant, higher risk for cardiovascular events incidence in AAC-positive, low-AAC, and high-AAC when compared to the control group.

Interpretation: AAC assessed with routine VFA was shown to be a strong predictor for cardiovascular events.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Absorptiometry, Photon*
  • Adult
  • Aged
  • Aorta, Abdominal / diagnostic imaging*
  • Aorta, Abdominal / pathology*
  • Calcinosis / diagnostic imaging*
  • Calcinosis / pathology*
  • Cardiovascular Diseases / epidemiology*
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Lumbar Vertebrae / diagnostic imaging
  • Male
  • Middle Aged
  • Osteoporosis / diagnostic imaging
  • Predictive Value of Tests
  • Proportional Hazards Models