Body mass index as a predictor of the presence but not the severity of coronary artery disease evaluated by cardiac computed tomography

Hélder Alexandre Correia Dores*, Pedro de Araújo Gonçalves, Maria Salomó Carvalho, Pedro Jerónimo Sousa, António Ferreira, Nuno Cardim, Miguel Mota Carmo, Ana Aleixo, Miguel Mendes, Francisco Pereira Machado , José Roquette, Hugo Marques

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

Background: The relation between body mass index (BMI) and coronary artery disease (CAD) extension remains controversial. The aim of this study was to evaluate the correlation between BMI and CAD extension documented by coronary computed tomography angiography (CCTA). Methods and results: Prospective registry including 1706 consecutive stable patients that performed CCTA (dual source scanner) for the evaluation of CAD. The population was stratified by BMI: normal 530 (31.1%), overweight 802 (47.0%) and obesity 374 (21.9%). BMI was significantly higher in patients with CAD (27.7 ± 4.3 vs 26.8 ± 4.3 kg/m(2), p 5 segments with plaque (15.4% patients). The prevalence of SIS >5 among the BMI classes was: 18.7%, 13.7% and 13.6% for normal, overweight and obesity respectively (p values for the specific classes versus all other patients: 0.241, 0.450 and 0.663). Conclusions: In this population of stable patients undergoing CCTA for suspected CAD, BMI was an independent predictor of its presence, but was not correlated with the coronary disease severity.
Original languageEnglish
Pages (from-to)1387-1393
Number of pages7
JournalEuropean Journal of Preventive Cardiology
Volume21
Issue number11
DOIs
Publication statusPublished - 11 Nov 2014
Externally publishedYes

Keywords

  • Body mass index
  • Cardiac computed tomography
  • Coronary artery disease
  • coronary artery disease
  • body mass index

Fingerprint

Dive into the research topics of 'Body mass index as a predictor of the presence but not the severity of coronary artery disease evaluated by cardiac computed tomography'. Together they form a unique fingerprint.

Cite this