부산대학교 도서관

Background: Recent studies have shown that microalbuminuria (MAU) refl ected in a higher probability of cardiovascular disease for cardiovascular risk assessment. We aimed to question the availability of microalbuminuria in metabolically healthy obese patients as a predictor of diastolic dysfunction to assess the cardiovascular risk. Methods: 100 obese patients without accompanying diseases were included in the study. They were screened for any signs of acute/chronic inflammation and those having any were excluded. None of the patients were on any medications infl uencing diastolic dysfunction. Blood glucose, HbA1c, urea, creatinine, total cholesterol, LDL, HDL, triglyceride and 24-hour-urine microalbuminuria and creatinine clearance (GFR) levels were studied. Two-dimensional doppler echocardiography was performed. Data was statistically analyzed using SPSS Windows 11.5. Results: Statistical analysis showed that there was no signifi cant difference between patients with diastolic dysfunction and normal echocardiograpghy fi ndings when compared for MAU and also for BMI. In all groups, there was no relation between MAU and BMI according to correlation analysis. There was statistically significant difference for age (p<0,0001), glucose (p=0,019), total cholesterol (p=0,009) and LDL (p=0,019) and no difference for gender, smoking, HbA1c, HDL, systolic and diastolic blood pressure, creatinine, GFR and triglyceride (p>0,05) between groups. Conclusions: Microalbuminuria found in obese patients can be related with diastolic dysfunction which might refl ect subclinical cardiac damage with a simple method and in advance. The lack of demonstration of this relationship in our study might be due to limited number of patients included and especially low percentage of patients with microalbuminuria. But the relationship found for blood glucose and lipid parameters still can show metabolic tendency. If an approval of this relationship can be achieved by studies with a higher number of patients, an easy and non-invasive method to predict obesity cardiomyopathy might be possible.