Objectives: The aim of this study was to evaluate renal functional impairment in diabetic nephropathy using ultrasonographic indices of the kidney.
Subjects and Methods: We enrolled 57 patients (mean age 60±17 years, 65% male) who were clinically diagnosed with type 2 diabetes and underwent abdominal ultrasonography at our hospital. Patients were classified based on the Classification of Diabetic Nephropathy as revised in December 2013. Out of the total 57 patients, 23 were stage 1, 16 patients were stage 2, 8 patients were stage 3, and 10 patients were stage 4. We evaluated kidney size, renal peripheral vascular resistance index (RI), and renal cortical brightness using a Logiq 7 Ultrasound device (GE health care Japan). Renal cortex brightness was quantitatively evaluated using iPlaque® developed at our hospital.
Result and Discussions: There was no significant difference in kidney size between any groups. The RI was significantly different between stage 1 and 3, stage 1 and 4, and stage 2 and 4 (p＜0.05); a weak correlation was found between the stages and RI (ρ＝0.472, p＜0.05). The renal cortical brightness was significantly different between all groups (p＜0.05), and stages (ρ＝0.736, p＜0.05). Urinary albumin was significantly correlated with RI and renal cortical brightness; among them, renal cortical brightness was the most correlated (r＝0.57, p＜0.001). eGFR was significantly correlated with all of the indices, and renal cortical brightness showed the best correlation (r＝−0.59, p＜0.001). Consequently, we determined that renal cortical brightness is a useful parameter for evaluating diabetic nephropathy because it increased from the early stage and correlated with stage progression.
Conclusions: In diabetic nephropathy, renal cortical brightness is the most useful index to reflect the disease stage.
Purpose: Epicardial adipose tissue (EAT) is ectopic fat surrounding the coronary arteries. Our previous study reported that EAT in the anterior interventricular groove (EAT-AIG) can be visualized and used as a marker of coronary artery disease. This study was conducted at a single center; thus, it was not a multicenter validation study. Here we conducted a multicenter trial to determine interobserver variability of EAT-AIG measurements.
Subjects and Methods: To examine the interobserver variability, three sonographers at different cardiovascular hospitals measured the EAT-AIG thickness in 12 volunteers (mean age: 61±22 years, 8 males). The measurement of EAT-AIG thickness was performed using a linear ultrasound probe (Vivid E9). To measure EAT-AIG thickness, we used a modified low parasternal long-axis view. EAT-AIG thickness was measured as the distance from the myocardium to the visceral layer of the epicardium, perpendicular to the pericardium. All sonographers were blinded to each other’s interpretation. We used Bland–Altman analysis and the intraclass correlation coefficient (ICC) to determine the variation of EAT-AIG thicknesses among the three sonographers.
Results and Discussion: There was a good correlation between all of the measurements. The measurements of EAT-AIG thickness by the three sonographers were highly correlated (ICC: 0.90, 95% confidence interval: 0.78–0.97, p＜0.01). However, we found one case which we determined to be an outlier. The outlier measurement of EAT-AIG thickness was measured in the apical view and not in the modified low parasternal long-axis view.
Conclusions: Echocardiographic measurements of EAT-AIG thickness significantly varied, with linear measurements showing the least variability among the three sonographers. These findings should considered when evaluating the clinical and scientific significance of longitudinal, repeated measurements of EAT-AIG thickness.