To Örebro University

INTRODUCTION: Psoriatic arthritis (PsA) is associated with increased cardiovascular (CV) risk and mortality. Aortic stiffness measured by carotid-femoral pulse wave velocity (cfPWV) has been shown to predict CV risk in the general population. The present study aimed to examine cfPWV values of patients with PsA compared to healthy controls and to evaluate associations of cfPWV with patient- and disease-associated characteristics, as well as with an established traditional CV prediction score of the European Society of Cardiology (Systemic Coronary Risk Evaluation; SCORE), for the first time.

METHODS: cfPWV and SCORE were evaluated in patients with PsA and healthy controls, along with clinical and laboratory disease parameters. Differences in cfPWV measurements between the two groups and associations of cfPWV with patient- and disease-associated characteristics were statistically evaluated.

RESULTS: A total of 150 patients with PsA (PSOCARD cohort) and 88 control subjects were recruited. cfPWV was significantly higher in the PsA group compared to controls, even after adjustment for confounders (padj = 0.034). Moreover, cfPWV was independently associated with disease duration (r = 0.304, p = 0.001), age (rho = 0.688, p < 0.001), systolic arterial pressure (rho = 0.351, p < 0.001), glomerular filtration rate (inverse: rho = - 0.264, p = 0.001), and red cell distribution width, a marker of major adverse CV events (MACE) (rho = 0.190, p = 0.02). SCORE revealed an elevated CV risk in 8.73% of the patients, whereas cfPWV showed increased aortic stiffness and end-organ disease in 16.00% of the same cohort.

CONCLUSIONS: In the largest cfPWV/PsA cohort examined to date, patients with PsA exhibited increased aortic stiffness compared to healthy controls. PsA duration was the most important independent disease-associated predictor of increased aortic stiffness, next to traditional CV risk factors. cfPWV measurements may help identify subclinical end-organ disease and abnormal aortic stiffness and thus assist CV risk classification in PsA.