Carotid plaque thickness predicts cardiovascular events and death in patients with chronic kidney disease - Sasha S. Bjergfelt; Ida M. H. Sørensen; Laerke Urbak; Klaus F. Kofoed; Theis Lange; Bo Feldt-Rasmussen; Henrik Sillesen; Christina Christoffersen; Susanne Bro (BMC Nephrology)
Abstract Background Classical risk scoring systems underestimate the risk of cardiovascular disease in chronic kidney disease (CKD). Coronary artery calcium score (CACS) has improved prediction of cardiovascular events in patients with CKD. The maximal carotid plaque thickness (cPTmax) measured in ultrasound scans of the carotid arteries has demonstrated similar predictive value as CACS in the general population. This is the first study to investigate whether cPTmax can predict cardiovascular events in CKD and to compare the predictive value of cPTmax and CACS in CKD. Method Two hundred patients with CKD stage 3 from the Copenhagen CKD Cohort underwent ultrasound scanning of the carotid arteries. The assessment consisted of locating plaque and measuring the thickest part of the plaque, cPTmax. Based on the distribution of cPTmax, the participants were divided into 3 groups: No plaques, cPTmax 1.0–1.9 mm and cPTmax > 1.9 mm (median cPTmax = 1.9 mm among patients with plaques). To measure CACS, 175 of the patients underwent a non-contrast CT scan of the coronary arteries. The follow-up time spanned between the ultrasound scan and a predefined end-date or the time of first event, defined as a composite of major cardiovascular events or death of any cause (MACE). Results The median follow-up time was 5.4 years during which 45 patients (22.5%) developed MACE. In a Cox-regression adjusted for classical cardiovascular risk factors, patients with cPTmax > 1.9 mm had a significantly increased hazard ratio of MACE (HR 3.2, CI: 1.1–9.3), p = 0.031) compared to patients without plaques. C-statistics was used to evaluate models for predicting MACE. The improvement in C-statistics was similar for the two models including classical cardiovascular risk factors plus cPTmax (0.247, CI: 0.181–0.312) and CACS (0.243, CI: 0.172–0.315), respectively, when compared to a model only controlled for time since baseline (a Cox model with no covariates). Conclusion Our results indicate that cPTmax may be useful for predicting MACE in CKD. cPTmax and CACS showed similar ability to predict MACE.