Article Text
Abstract
Background Carotid ultrasonography (CU) and coronary artery calcification score (CAC) evaluated by multidetector computed tomography (MDCT) scanner are useful in detecting subclinical atherosclerosis and are good surrogate markers of cardiovascular morbidity and mortality in general population and in rheumatoid arthritis (RA). In RA, a good correlation between both diagnostic methods has been demonstrated, being CU more sensitive for detecting subclinical atherosclerosis.
Objectives Our aim is to determine the association between the presence of carotid plaque and CAC quantification, and, using the presence of carotid plaque as a reference, to determine the cut-off value of CAC score that better predicts subclinical carotid atherosclerosis.
Methods We evaluated 127 RA patients without previous cardiovascular events. Carotid ultrasonography was performed by a MyLab 70 scanner (Esaote; Genoa, Italy), equipped with 7–12 MHz linear transducer and the automated software guided technique radiofrequency – Quality Intima Media Thickness in real-time (QIMT, Esaote, Maastricht, Holland). Carotid plaque was defined according to the Manheim Conference Consensus criteria. To determine CAC score, a CT Imaging of coronary arteries using a 32-slice MDCT scanner (Lightspeed, Pro 32, GE Healthcare, USA) was performed. A CAC score ≥100 was considered as a surrogate marker of very high cardiovascular risk.
Results Unilateral and bilateral carotid plaque frequency and the mean CAC score in the different groups are summarized in table 1. Patients without carotid plaques had a mean CAC value of 23 ±49 [range 0–250], being 50 ±116 [0–569] in patients with unilateral plaque and 192± 302 [0–1205] in patients with bilateral plaques, being these differences statistically significant (p<0.001). Using a CAC score ≥100 as a marker of very high cardiovascular risk, the sensitivity to detect carotid plaques was very low (28%).
A ROC curve comparing the presence of carotid plaque and CAC quantification was performed, being the area under the curve 0.692. When we used CAC score value score ≥1 as the cut-off value to predict high cardiovascular risk, the sensitivity and specificity for the presence of carotid plaques increased (69.3% and 64.1%, respectively). Positive predictive value for CAC ≥1 was 81.3% in our population, being 48.1% the negative predictive value.
Regarding bilateral carotid plaques, the CAC score ≥100 had a sensitivity of 40%. ROC curve showed an area under the curve of 0.712. Using a CAC score value score ≥1 as the cut-off value to predict high cardiovascular risk, the sensitivity to determine the presence of carotid plaques increased to 76.4% but the specificity decreased to 54.2%.
Conclusions A CAC score value score ≥1 is good predictors of carotid plaques, showing sensitivity close to 70%. Our data support the use of a CAC score value score ≥1 instead of a CAC score ≥100 as the cut-off value to predict high cardiovascular risk in patients with RA.
Disclosure of Interest None declared