Assessment of abdominal aortic calcification by computed tomography for prediction of latent left ventricular stiffness and future cardiovascular risk in pre-dialysis patients with chronic kidney disease: A single center cross-sectional study.

Introduction

There is general interest in finding clinical markers for left ventricular diastolic dysfunction (LVDD), a major cause of cardiorenal syndrome leading to heart failure in chronic kidney disease (CKD) patients. The aim was to assess the utility of computed tomography (CT)-based abdominal aortic calcification (AAC) for the prediction of LVDD and prognosis of asymptomatic pre-dialysis CKD patients. Materials and methods: We prospectively evaluated 218 pre-dialysis CKD patients [median estimated glomerular filtration rate (eGFR); 40.9 mL/min/1.73m²]. Non-contrast CT scan and echocardiography were performed to determine the aortic calcification index (ACI) as a semi-quantitative measure of AAC.

Results

The median ACI was 11.4. AAC and LVDD were diagnosed in 193 patients (89%) and 75 patients (34%), respectively. Using receiver operating characteristic curve analysis for the estimation of LVDD, ACI of 20 showed optimal sensitivity (52.0%) and specificity (62.8 %) (AUC = 0.664, p < .001). High ACI group included more patients with LVDD-related factors, such as old age, hypertension, diabetes, and more severe CKD. LVDD was significantly more common in patients with high ACI group [39 (50%) and 36 (26%), respectively, p<0.001]. Multivariate analysis showed that ACI correlated significantly with E/A (β=-0.993, p=0.003), E/e' (β=0.077, p<0.001), and cardio-ankle vascular index (β=0.209, p=0.001). Correspondingly, E/e' correlated with logBNP and log(ACI+1), and increased proportionately and significantly with the quartiles of ACI values. Cox proportional hazard models showed that ACI was an independent predictor of CV outcome (hazard ratio 1.03, 95% confidence interval 1.00-1.06, p=0.029).

Conclusion

The results would suggest the usefulness of AAC assessment by CT to predict latent LVDD and future CV risk in asymptomatic pre-dialysis CKD patients.