Individualized prediction of risk of ascending aortic syndromes

PLoS One. 2022 Jun 27;17(6):e0270585. doi: 10.1371/journal.pone.0270585. eCollection 2022.

Abstract

Objectives: Although ascending aortic diameter changes acutely after dissection, recommendation for prophylactic surgery of thoracic aortic aneurysms rely on data from dissected aortas. In this case-control study we aim to identify risk markers for acute and chronic aortic syndromes of the ascending aorta (ACAS-AA). Furthermore, to develop a predictive model for ACAS-AA.

Methods: We collected data of 188 cases of ACAS-AA and 376 controls standardized to age- and sex of the background population. Medical history and CT-derived aortic morphology were collected. For the dependent outcome ACAS-AA, potential independent risk factors were identified by univariate logistic regression and confirmed in multivariate logistic regression. As post-dissection tubular ascending aortic diameter is prone to expand, this factor was not included in the first model. The individual calculated adjusted odds ratios were then used in ROC-curve analysis to evaluate the diagnostic accuracy of the model. To test the influence of post-ACAS-AA tubular ascending aortic diameter, this was added to the model.

Results: The following risk factors were identified as independent risk factors for ACAS-AA in multivariate analysis: bicuspid aortic valve (OR 20.41, p = 0.03), renal insufficiency (OR 2.9, p<0.01), infrarenal abdominal aortic diameter (OR 1.08, p<0.01), left common carotid artery diameter (OR 1.40, p<0.01) and aortic width (OR 1.07, p<0.01). Area under the curve was 0.88 (p<0.01). Adding post-ACAS-AA tubular ascending aortic diameter to the model, negated the association of bicuspid aortic valve, renal insufficiency, and left common carotid artery diameter. Area under the curve changed to 0.98 (p<0.01).

Conclusions: A high performing predictive model for ACAS-AA, free of ascending aortic diameter, can be achieved. Furthermore, we have identified abdominal aortic ectasia as an independent risk factor of ACAS-AA. Integration of potential biomarkers and morphologic variables, derived from undissected aortas, would probably improve the model.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aorta, Abdominal
  • Bicuspid Aortic Valve Disease*
  • Case-Control Studies
  • Humans
  • Renal Insufficiency*
  • Syndrome

Grants and funding

The project was funded by the University of Southern Denmark and the A.P. Møller Foundation for the Advancement of Medical Science (17-L-0042) in the form of grants to QWS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.