Greyscale, colour Doppler and oscillometric macroangiopathy indices in patients with autoinflammatory syndromes: the INFLAMMACARD cohort

Objectives To evaluate for the first time a combination of novel colour Doppler ultrasound (CDUS), greyscale (GSUS) and oscillometric indices of angiopathy in patients with autoinflammatory syndromes (AIS). Further, to explore the associations between these markers and patient- and disease-related characteristics, as well as traditional cardiovascular (CV) risk factors. Methods CDUS was used to assess arterial compliance markers, such as resistance index, pulsatility index (PI) and flow-velocity integral (FVI) in the common carotid artery (CCA) of AIS patients and healthy controls. Additionally, GSUS was employed to measure carotid intima-media thickness (cIMT), detect plaques and quantify total calcification surface. Oscillometry was utilized to evaluate aortic stiffness by carotid-femoral pulse wave velocity (cfPWV). Results Thirty-one patients with AIS and 62-matched (1:2) healthy controls were recruited. AIS patients exhibited higher CCA-PI [1.89 (0.46) vs 1.59 (0.32), P = 0.024] and peak systolic velocity (80.15 vs 64.95 cm/s, P = 0.003), compared with controls. Moreover, AIS patients not receiving biologic therapy demonstrated significantly higher cfPWV [6.99 (1.71) vs 5.86 (0.81) m/s, P = 0.001]. cfPWV and cIMT were predicted by age (cfPWV: rho = 0.573, P < 0.001; cIMT: rho = 0.675, P = 0.002), systolic arterial pressure (SAP) (cfPWV: r = 0.464, P = 0.009; cIMT: rho = 0.514, P = 0.029) and lymphadenopathy (cfPWV: eta = 0.373, P = 0.039). PI associated with nicotine (rho = 0.691, P = 0.008) and FVI (inversely) with SAP (rho = -0.522, v0.026). Conclusion In the first CV surrogate marker study in AIS combining oscillometry and arterial US, patients exhibited increased carotid pulsatility and altered flow dynamics vs controls. Aortic stiffness was lower in patients receiving biologics and mainly predicted by traditional CV factors and lymphadenopathy. Angiopathy markers may reveal significant vascular abnormalities in AIS patients, improving CV screening and risk classification.