sawai akihiro

The purpose of this study was to investigate the relationship between abdominal aortic calcification (AAC) and coronary artery calcification (CAC) in chronic kidney disease (CKD) patients. We evaluated 126 asymptomatic CKD patients (mean estimated glomerular filtration rate: 36.1 +/- A 14.1 mL/min/1.73 m(2), mean age 70.3 +/- A 10.1 years). A non-contrast computed tomography scan was used to determine the abdominal aortic calcification index (ACI) and CAC score, and this relationship was investigated. Among the subjects, AAC was present in 109 patients (86.5 %) as defined by ACI > 0 and median ACI was 11.7 %. ACI increased in accordance with advances in CAC score grades (3.0, 5.2, 17.2, and 32.8 % for CAC score 0, 1-100, 101-400, and 401 or more, respectively, p < 0.001). Even after multivariate adjustment, ACI was independently associated with severe CAC score as defined by CAC score > 400 [odds ratio 1.08, 95 % confidence interval (CI) 1.04-1.12, p < 0.001]. Receiver-operating curve analysis showed that the ACI optimal cut-off value predicting severe CAC score was 16.5 % (area under the curve = 0.79, 95 % CI 0.69-0.90, p < 0.001). The C statics for predicting CAC score was significantly increased by adding ACI values to the model including other risk factors (0.853 versus 0.737, p = 0.023). In conclusion, the ACI value of 16.5 % allows us to predict the presence of severe CAC in CKD patients, and that the addition of ACI to the model with traditional risk factors significantly improves the predictive ability of severe CAC score. These data reinforce the utility of ACI as a screening tool in clinical practice.

The clinical usefulness of physiological and radiological examinations for cardiovascular disease (CVD) risk stratification has not been fully demonstrated in chronic kidney disease (CKD) patients. In the present study, predictive values of CVD were investigated among asymptomatic CKD patients by comprehensive and non-invasive CVD screening programs. We prospectively evaluated 139 asymptomatic CKD patients. All patients were examined by comprehensive and non-invasive CVD risk screening programs that included carotid ultrasonography, coronary artery calcification score (CACS), pulse wave velocity, and flow-mediated vasodilation, and their associations with major adverse cardiovascular events (MACEs) were analyzed. During the median follow-up of 32.3 months, 13 MACEs were observed. Among all CVD screening examinations, severity of the carotid plaque score (PS) and CACS was significantly higher in the MACE group than in the MACE-free group (11.3 +/- A 5.8 versus 6.1 +/- A 5.3, P = 0.001 and 657 versus 74, P = 0.020, respectively). Kaplan-Meier curves for the incidences of MACEs classified according to the combination of carotid PS and CACS showed that severe carotid PS and severe CACS groups had the highest event rate in comparison with the groups without any of these (29.9, 11.9, and 3.6 %, respectively, P < 0.001). In this long-term follow-up analysis, the combination of carotid atherosclerosis and CACS was a useful and non-invasive screening tool for predicting cardiovascular events among asymptomatic CKD patients.

Background: The presence of abdominal aortic calcification (AAC) can predict cardiovascular (CV) outcomes in hemodialysis patients. However, little is known about the predictive value of AAC for CV outcomes in chronic kidney disease (CKD) patients without hemodialysis. The aim of this study was to investigate the prevalence and the predictive value of AAC in asymptomatic CKD patients. Methods: We prospectively evaluated 347 asymptomatic CKD patients without hemodialysis [median estimated glomerular filtration rate (eGFR): 43.2 mL/min/1.73 m(2)]. A non-contrast computed tomography scan was used to determine the abdominal aortic calcification index (ACI) as a semi-quantitative measure of AAC. The patients were divided into three groups according to the tertiles of ACI. Results: Among the subjects, AAC was found (ACI >0) in 296 patients (86.3%), and the median ACI was 11.4%. During the median follow-up of 41.5 months, a total of 33 CV events were observed. Patients with the highest tertile of ACI had the highest risk of CV outcomes compared with the other two groups (96.5%, 93.0%, and 74.3%, respectively; p < 0.001). The Cox proportional hazard models showed that ACI was an independent predictor of CV outcomes (hazard ratio 1.36, 95% confidence interval 1.17-1.60, p < 0.001). The C-index was also significantly increased by adding eGFR and ACI values to the model along with the other conventional risk factors (0.79 versus 0.66, p = 0.043). Conclusion: Evaluation of the AAC provides useful information for predicting adverse clinical outcomes among asymptomatic CKD patients without hemodialysis. (C) 2015 Elsevier Ireland Ltd. All rights reserved.