scholarly journals Multi-electrode endovascular denervation at a new site of celiac artery for glycemic control in patients with type 2 diabetes mellitus: a promisingly primary result

2021 ◽  
Author(s):  
Tao Pan ◽  
Qiong Wei ◽  
Zhi Wang ◽  
Qi Zhang ◽  
Yue Qian ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Glycemic Control ◽  
Abdominal Aorta ◽  
Celiac Artery ◽  
C Peptide ◽  
Catheter System

Abstract Background: Although renal denervation (RDN) may theoretically be effective on type 2 diabetes mellitus (T2DM), most clinical data failed to demonstrate such a concept. We investigated the safety and primary effects of catheter-based endovascular denervation (EDN) at new sites of the celiac artery (CA), and the abdominal aorta around CA using a novel multi-electrode device on glycemic control in T2DM patients. Methods: With a novel six-electrode catheter system, EDN was conducted in T2DM patients at new sites of CA and aorta between CA and superior mesenteric artery (SMA) in purpose of targeting on the postganglionic efferent nerves innervating the liver, islet, and other metabolic organs. The major inclusion criteria were T2DM patients diagnosed over 5 years, with hemoglobin A1c (HbA1c) over 7.5%. The primary outcomes were evaluated by the safety, HbA1c, homeostasis-model assessment of insulin resistance (HOMA-IR), fasting plasma glucose (FPG), 2-hour postprandial plasma glucose (2hPG), and oral glucose tolerance test (OGTT) based 3-hour C-peptide test. The antidiabetic medication, lifestyle, physical condition, blood pressure (BP), plasma norepinephrine, angiotensin II, liver biochemistry, and plasma lipids were also recorded.Results: A total of 11 patients were included for analysis. The technical success was 100% and no severe treatment-related adverse events or major complications were observed. Both HbA1c and HOMA-IR significantly reduced at 6 months (9.9 vs. 8.0, P = 0.005; 13.3 vs. 6.0, P = 0.016, respectively). Decreases of FPG and 2hPG were observed (15.4 vs.10.1 mmol/L, P < 0.001; 17.9 vs. 11.4 mmol/L, P = 0.001, respectively). OGTT based C-peptide test indicated improved beta-cell function ([AUC] 0.23 vs. 0.28 pmol/mL, P =0.046). A reduction of daily insulin injection (P = 0.02) and improvement of liver function (ALT, P = 0.014; GGT, P = 0.021) were also observed without changes in lifestyle, physical conditions, and other metabolic measurements.Conclusions: The 6-month analysis of this trial showed that EDN at new sites of CA and the abdominal aorta around celiac artery using the novel six-electrode catheter system elicits a clinically significant improvement in glycemic control and insulin resistance in patients with T2DM, with good tolerability. Trial Registration Number NCT 04086043, dated 11/9/2019.

scholarly journals Correlation Between Lipid Profile with Type 2 Diabetes Mellitus Progression

2020 ◽  
Vol 8 (2) ◽  
pp. 66-72
Author(s):  
Angiesta Pinakesty ◽  
Restu Noor Azizah
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Glycemic Control ◽  
Lipid Profile ◽  
Cholesterol Levels ◽  
Type 2 Dm ◽  
Hba1c Levels

Introduction: Diabetes mellitus (DM) is a non-communicable disease that has increased from year to year. Type 2 diabetes mellitus is not caused by lack of insulin secretion, but is caused by the failure of the body's cells to respond to the hormone insulin (insulin resistance). Insulin resistance was found to be a major contributor to atherogenic dyslipidemia. Dyslipidemia in DM risks 2 to 4 times higher than non-DM. Although dyslipidemia has a great risk for people with type 2 diabetes mellitus, this conventional risk factor only explains a portion (25%) of excess cardiovascular risk in type 2 DM. Discussion: In uncontrolled type 2 DM patients, LDL oxidation occurs faster which results from an increase in chronic blood glucose levels. Glycemic control as a determinant of DM progressivity is determined through HbA1c examination. HbA1c levels are associated with blood triglyceride levels. Meanwhile, triglyceride levels are associated with total cholesterol and HDL cholesterol levels. HbA1c levels are also associated with LDL cholesterol levels. Conclusion: There is a relationship between lipid profile and the progression of type 2 diabetes mellitus.   Keywords: type 2 diabetes mellitus, dyslipidemia, HbA1c, glycemic control, lipid profile

Effects of Pinitol on Glycemic Control, Insulin Resistance and Adipocytokine Levels in Patients with Type 2 Diabetes Mellitus

2012 ◽  
Vol 60 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Hyun Jin Kim ◽  
Kang Seo Park ◽  
Seong Kyu Lee ◽  
Kyung Wan Min ◽  
Kyung Ah Han ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Glycemic Control

scholarly journals Effects of Encapsulated Propolis on Blood Glycemic Control, Lipid Metabolism, and Insulin Resistance in Type 2 Diabetes Mellitus Rats

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Yajing Li ◽  
Minli Chen ◽  
Hongzhuan Xuan ◽  
Fuliang Hu
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Body Weight ◽  
Lipid Metabolism ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Density Lipoprotein

The present study investigates the encapsulated propolis on blood glycemic control, lipid metabolism, and insulin resistance in type 2 diabetes mellitus (T2DM) rats. The animal characteristics and biological assays of body weight, fasting blood glucose (FBG), fasting serum insulin (FINS), insulin act index (IAI), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured and euglycemic hyperinsulinemic glucose clamp technique were used to determine these effects. Our findings show that oral administration of encapsulated propolis can significantly inhibit the increasing of FBG and TG in T2DM rats and can improve IAI and M value in euglycemic hyperinsulinemic clamp experiment. There was no significant effects on body weight, TC, HDL-C, and LDL-C in T2DM rats treated with encapsulated propolis. In conclusion, the results indicate that encapsulated propolis can control blood glucose, modulate lipid metabolism, and improve the insulin sensitivity in T2DM rats.

scholarly journals The association of anthropometric parameters with markers of insulin and leptin secretion and resistance in type 2 diabetes mellitus

2020 ◽  
Vol 28 (3) ◽  
pp. 299-314
Author(s):  
Simona Cernea ◽  
Emőke Both ◽  
Adriana Fodor
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Insulin Secretion ◽  
Diabetes Duration ◽  
Leptin Resistance ◽  
Anthropometric Parameters ◽  
C Peptide

AbstractAim: We evaluated the association between anthropometric parameters and markers of insulin and leptin secretion/resistance in patients with type 2 diabetes mellitus (T2DM).Material and methods: This post-hoc data analysis from a cross-sectional study included 176 T2DM patients. Laboratory tests (serum leptin, soluble form of leptin receptor (sObR), C peptide, glycemic and lipid parameters) and anthropometric parameters were obtained, adiposity indexes (including body adiposity index (BAI), visceral adiposity index (VAI)), indicators of insulin resistance, β-cell function, and leptin resistance (Free Leptin Index, FLI) were calculated.Results: The body mass index (BMI), diabetes duration, VAI and leptin correlated independently with HOMA-IR, while BMI, diabetes duration and HbA1c with HOMA-B. The total body fat mass (TBFM), C peptide, diabetes duration, BMI and BAI correlated with leptin concentrations, while the first three with FLI. VAI was an indicator of insulin resistance (β=0.166, p=0.003), while BAI of leptin secretion (β=0.260, p=0.010). TBFM strongly associated with leptin resistance and secretion (β=0.037, r=0.688, p<0.0001, and β=0.521, r=0.667, p<0.0001), and BMI correlated weakly with insulin secretion and resistance. While insulin and leptin secretion increased progressively with BMI, leptin and insulin resistance became significant only in case of obesity. The sObR was significantly associated with C peptide concentrations (β=-0.032; p=0.044), but not with HOMA-B or -IR. A strong positive correlation between the C peptide/leptin ratio and non-fat mass /TBFM ratio was noted (r=0.62 [0.52, 0.71], p<0.0001).Conclusions: Parameters of peripheral adiposity correlated better with markers of leptin system, and those of visceral adiposity with markers of insulin secretion/resistance. The sObR correlated independently and negatively with C peptide.

scholarly journals The insulin resistance indices: necessity and opportunities in type 2 diabetes mellitus management

2020 ◽  
Vol 96 (7) ◽  
pp. 529-535
Author(s):  
Yu. A. Sorokina ◽  
O. V. Zanozina ◽  
A. D. Postnikova
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Clinical Practice ◽  
Glycemic Control ◽  
Metabolic Disorders ◽  
Glycosylated Hemoglobin ◽  
Tissue Sensitivity

The article provides a review of the literature on the possibilities of using various indices of insulin resistance in type 2 diabetes (T2DM) treatment. The main mechanisms of insulin resistance and its role in the formation of type 2 diabetes mellitus and other metabolic disorders are described. The main indices of insulin resistance, used in real clinical practice nowadays, are considered. Methods of their calculation are given. The effect of metformin and incretin active medications on insulin resistance is described. It was shown that the combination of these medications improves tissue sensitivity to insulin in patients with T2DM. Standard indicators for assessing glycemic control, such as fasting glucose and glycosylated hemoglobin (HbA1c), do not reflect the patient’s lipid metabolism. The use of insulin resistance assessment indices in patients with type 2 diabetes mellitus allows both, exercising glycemic control, and the metabolic disorders, often associated with carbohydrate metabolism disorders, monitoring. Using insulin resistance indices, it is possible to select the optimal treatment regimen for type 2 diabetes mellitus for a particular patient, to predict and evaluate the effectiveness of treatment in dynamics. Simple, generally available laboratory indicators and anthropometric data are used to calculate the indices of insulin resistance, and they are easy to measure. In this regard, the use of insulin resistance indices is possible in routine clinical practice.

scholarly journals Comparison of Insulin Resistance in Lean and Obese Adults with Type 2 Diabetes Mellitus- A Cross-sectional Study

2020 ◽  
Author(s):  
Sandinti Deepa ◽  
V Lakshmaiah ◽  
K Prabhakar ◽  
A Raveesha ◽  
CR Vidyasagar ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Fasting Insulin ◽  
Obese Adults ◽  
Cross Sectional ◽  
Univariate Logistic Regression Analysis ◽  
C Peptide

Introduction: Insulin Resistance (IR) can develop into type 2 diabetes mellitus and is closely associated with obesity. However, the non-obese population has also shown a predisposition to the risk of IR due to genetics. Aim: To assess the relationship between IR and obesity in Type 2 Diabetes Mellitus (T2DM) by comparing the proportion of subjects with IR in lean and obese T2DM and to identify the factors predicting IR in T2DM. Materials and Methods: A cross-sectional, hospital-based study was done at Department of Medicine of RL Jalappa hospital, Kolar, Karnataka on 106 T2DM patients aged >18 years. The study population was grouped into lean (BMI <19 kg/m2) and obese adults (BMI >30 kg/m2). IR was calculated using Homeostasis Model Assessment-Insulin Resistance (HOMA-IR) and was considered as primary outcome variable. Obesity was considered as primary explanatory variable. Age, Gender, fasting insulin, C-peptide, Fasting Blood Sugar, Glycated haemoglobin (GHB or HbA1c) were the other explanatory variables. Descriptive analysis was carried out using mean and standard deviation for quantitative variables, frequency and proportion for categorical variables. Chi-square test was used to test statistical significance between the groups. Univariate logistic regression analysis was done to identify the predictors of IR. IBM Statistical Package for Social Sciences (SPSS) version 22 was used for statistical analysis. The p-value <0.05 was considered to be statistically significant. Results: The 106 subjects involved in the study had a mean age of 53.88±9.21 years. 44 subjects (41.5%) had IR. Obese to lean diabetic patients were in the ratio of 1:4. The proportion of obese diabetic subjects was (n=84, 79.2%) whereas lean diabetics were (n=22, 20.8%). The proportion of obese diabetic subjects with IR was 38.1% while the proportion of lean diabetic subjects with IR was 54.55%, but this difference was statistically not significant (p=0.163). On univariate logistic regression analysis, fasting insulin (odds ratio of 2.442 with 95% CI of 1.665 to 3.851, p<0.001**) and C-peptide (odds ratio of 1.446 with 95% CI of 1.123, p=0.004) were statistically significant factors attributing to IR. Conclusion: There was no significant relationship between IR and obesity. IR was independently associated with Fasting insulin levels and C-peptide levels.

scholarly journals Association of Serum Adipokines Levels with Glycemic Control and Metabolic Dyslipidemia in Sudanese Patients with Type 2 Diabetes Mellitus

2020 ◽  
Author(s):  
Halima Babiikir Eltahir ◽  
Elmahadi Mohamed Ali ◽  
Abdelrahim Osman Mohamed
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Adipose Tissue ◽  
Glycemic Control ◽  
Total Cholesterol ◽  
Pearson Correlation ◽  
P Value

Abstract Background:The pathogenesis of type 2 diabetes mellitus is due to two major abnormalities including insulin resistance and dysfunction, which lead to the inability to regulate blood glucose level. Adiponectin is a hormone secreted by the adipose tissue and it takes part in glucose metabolism with insulin-sensitising properties. Low levels of adiponectin leads to reduction of fatty acid oxidation decreased glucose uptake in skeletal muscle cells and increased level of free fatty acids leading to insulin resistance. Leptin is another adipokine produced by adipose tissue involved in the control of food intake via its action on the hypothalamus, suppressing appetite and stimulating energy expenditure. Leptin plays a critical role in pathophysiology of type 2 diabetes mellitus.The aim of the study was to investigate the association of serum adipokines levels with glycemic control and metabolic dyslipidemia in Sudanese patients with type 2 diabetes mellitus.Methods: This was a case control study. 202 patients with type 2 diabetes and 102 non-diabetic controls participated after signing written consent. Weight (kg) and height (m) were measured thenthe body mass index (kg/m2) was determined. Blood samples were collected after an overnight fasting. FBG, HbA1c and lipid profiles were measured using enzymatic methods. Adiponectin and leptin were measured using sandwich ELISA.Results: Adiponectin concentrations was significantly lower in patients with type 2 diabetes compared with the controls (p<0.001) and it was inversely correlated with HbA1c (Pearson Correlation -.160, P value = 0.005), total cholesterol and LDL levels (P = 0.05) and direct correlated HDL levels (P = 0.05). Leptin concentrations was significantly higher in patients with type 2 diabetes compared with the controls (p<0.002) and it was positively correlated with HbA1c (Pearson Correlation .155, P value = 0.02), total cholesterol and LDL levels (P = 0.05), there were no correlation with HDL and TG levels. Patients had significantly higher fasting blood glucose, HbA1c levels, total cholesterol and LDL levels compared with the controls. Conclusion: Patients with type 2 diabetes mellitus had decreased levels of serum adiponectin, high levels of serum leptin. There were significant correlations found between adiponectin and leptin levels with glycemic control and metabolic dyslipidemia

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