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￭ S-423 ￭
Plasma aldosterone level and its metabolic implications in patients with type 2 diabetes
1Department of Internal Medicine, Gachon University Gil Medical Center, 2Department of Internal Medicine, Jeju National University Hospital
*Jeongyeon Won1, Soyeon Yoo2, Sang Ah Lee2, Gwanpyo Koh2, Dae Ho Lee1
Aldosterone is involved in not only the regulation of blood pressure and renal sodium handling, but also the pathogenesis of insulin resistance, suggest- ing the clinical relevance of the inhibition of renin-angiotensin-aldosterone system (RAAS) in insulin resistant conditions. To better characterize meta- bolic implication of RAAS, we measured plasma renin activity (PRA) and aldosterone (PA) level in patient with type 2 diabetes. All other treatments and metabolic evaluations were performed at the discretion of the responsible physicians according to local guidelines. In the present study, we ana- lyzed the data of 628 patients aged 18 or more years. Major exclusion criteria included renal failure, severe hepatic dysfunction, the use of spi- ronolactone, and other severe systemic illnesses. Both PRA and PA were correlated with the circulating levels of serum sodium, apolipoprotein B (ApoB), high sensitivity CRP (hsCRP), and ALT. On a multivariate analysis, PA showed a significant association with ApoB (β＝0.580, p＝＜0.001), ALT (β＝0.305, p＝0.006), and sodium (β＝-0.224, p＝0.035) after adjusting for multiple factors. In subgroup analyses according to the type of RAAS inhibition, the association of PA with ApoB and hsCRP was markedly attenuated in patient treated with angiotensin-converting enzyme inhibitor (ACEi) (n＝53) compared with that in patients treated with angiotensin receptor blocker (n＝187) or with no RAAS inhibitor therapy (n＝388). Our re- sults show that aldosterone has important implications for the pathophysiology of type 2 diabetes. Further studies are required to determine whether ACEi therapy is a metabolically better RAAS inhibition in patients with type 2 diabetes.
￭ S-424 ￭
Association between critical shear stress and vascular complications in type 2 diabetes
Yeungnam University hospital
*Junho Lee1, Hojin Kim2, Ilrae Park2, Choonghee Kim2, Junsung Moon2, Jisung Yoon1, Kyuchang Won2, Hyoungwoo Lee1
The critical shear stress (CSS) is defined as a minimum shear-stress required to disperse RBC aggregates. Increased RBC aggregation is associated with the pathogenesis of vascular disease. The objective of this study was to clarify the association CSS and diabetic microangiopathy. We conducted a cross-sectional study with 234 patients with T2DM who visited Yeungnam university hospital. Patients with end stage renal disease, malignancy and who were diagnosed diabetic ketoacidosis were excluded. CSS was measured with a Rheoscan-D (Rheo-Meditech, Seoul, Korea), a microfluidic hemorheometer. We divided the CSS into quartile (Q1,Q2,Q3, and Q4 from lowest to highest CSS). 209 patients (mean age 59.27±12.64 years, M:F＝
122:87) were finally included. Patients with microvascular complications had lower CSS compared with patients without any complications (CSS 287 vs. 345, p＝0.002). Of them, patients with retinopathy had lower CSS compared with patients without retinopathy (CSS 281 vs. 385, p＝0.00), whereas patients with nephropathy and neuropathy had no significant difference in CSS. After adjustment for age, sex, HbA1C, duration of diabetes, hemoglo- bin, hypertension, smoking, alcohol and lipids, higher CSS remained significantly associated with the prevalence of diabetic nephropathy (Odds ratio for Q1 compared with Q4, 12.329; 95% confidence interval, 1.882-80.775). In patients with T2DM, there were significant relationship between CSS and diabeticnephropathy. These results suggest that CSS could be a novel marker for predicting diabetic nephropathy.
Table 1. Baseline Characteristics of subjects (categorized into quartiles based on critical shear stress) Group 1 Group 2 Group 3 Group 4 CSS mean (mPa) 197.30±24.41 261.47±13.73 319.38±19.23 513.66±160.30 Age (yrs) 59.8±12.0 60.9±13.3 56.7±11.0 60.0±13.9 HbA1C (%)* 7.8±1.9** 8.1±2.0**
8.4±2.1 9.5±2.8 BMI (kg/m2) 23.5±2.3 23.7±3.9 24.4±3.1 24.2±4.6 Hemoglobin (g/dL)* 13.3±1.6 13.7±1.5** 14.4±1.5** 12.5±1.8 Hematocrit (%)* 39.1±5.2 40.2±4.7** 42.2±4.4** 36.7±5.5 Albumin (g/dL)* 4.5±0.5 4.6±0.6 4.5±0.5 3.7±0.9 Creatinine (mg/dL)* 1.07±0.39 1.01±0.33** 1.06±0.29 1.19±0.44 eGFR (ml/min/1.73 m2)* 76.2±21.6 80.1±21.4** 77.8±19.8** 66.4±26.1 Urine ACR (mg/g)* 48.1±157.5** 59.2±161.2** 89.2±336.5**
374.4±733.2 HOMA-IR 3.72±3.29 4.26±4.28 4.28±2.14 4.71±2.56 HOMA-B 30.95±19.50 44.84±30.60 35.21±24.90 34.12±22.93 Table 2. The odds ra- tio for microvascular complications, by multiple logistic regression analysis CSS quartiles 1st 2nd 3rd 4th Any microvascular complications Reference 1.21 (0.55, 2.64) 1.27 (0.57, 2.80) 2.73 (1.15, 6.48)* Nephropathy 2.08 (0.87, 4.97) 2.52 (1.06, 6.00)* 10.11 (4.09, 25.00)* Retinopathy 1.41 (0.63, 3.15) 0.96 (0.42, 2.19) 1.58 (0.70, 3.56) Neuropathy 1.10 (0.42, 2.86) 1.26 (0.49, 3.24) 1.86 (0.75, 4.62)
