1. Association of vascular function and estimated cardiovascular risk in patients with rheumatoid arthritis
- Author
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Herwig Pieringer, Erich Pohanka, Rudolf Puchner, and Tobias Brummaier
- Subjects
Artrite reumatoide ,Análise de onda de pulso ,Risco cardiovascular ,Score ,QRISK2 ,Diseases of the musculoskeletal system ,RC925-935 - Abstract
Abstract Objectives: Rheumatoid arthritis (RA) patients should receive cardiovascular (CV) risk assessment. For this purpose CV risk calculators are available. In addition, parameters of vascular function can be measured and used for risk prediction. Aim of the present study was to assess the association of these two concepts. Methods: 287 RA patients (58.4 ± 12.6 years) and 232 controls (49.9 ± 13.4 years) were included in this cross-sectional study. We calculated 10 year CV risk with SCORE and QRISK2. For SCORE we used the recommended multiplier of 1.5 in eligible RA patients and estimated the risk also in patients younger than 40 years (mSCORE (0-65)). Augmentation index (AIx) and central pulse pressure (PP), markers of vascular integrity and CV risk, were assessed by pulse wave analysis (PWA). Primary endpoint was the correlation of AIx and the estimated CV risk using mSCORE (0-65). Results: In RA patients AIx showed a statistically significant correlation with mSCORE (0-65) (rho = 0.3374; p < 0.0001) and QRISK2 (rho = 0.3307; p < 0.0001). The correlations of central PP with mSCORE (0-65) (rho = 0.4692; p < 0.0001) and QRISK2 (rho = 0.5828; p < 0.0001) were also statistically significant. Increasing quartiles of central PP were associated with an increased odds of being in the "high risk"category according to SCORE (OR 2.18; 95% CI 1.58-3.01) or QRISK2 (OR 2.18; 95% CI 1.75-2.72). In control patients we also found a correlation of AIx and central PP with SCORE (0-65) and QRISK2. Conclusions: Parameters of central haemodynamics correlate with calculated CV risk. However, both do not give exactly the same information. The question arises whether a combination of both concepts would result in an improved CV risk prediction.
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