Glycemic control of type 2 diabetic patients after short-term zinc supplementation

Hemoglobin A 1c and Fructosamine for Assessing Glycemic Control in Diabetic Patients With CKD Stages 3 and 4

Objective To explore the clinical features of type 2 diabetic patients with hypertension , and to analyze the influencing factors of glycemic control. Methods Using stratified cluster random sampling method, 5 communities were selected from urban areas of Huai'an in 2014. Type 2 diabetic patients managed by the communities were surveyed with questionnaire, physical and biochemical examinations. The related information and clinical features were compared between diabetic patients with and without hypertension. Logistic regression analysis was used to analyze the influencing factors of glycemic control. Results The number of well-controlled diabetic patients (HbA1c<7.0%) with and without hypertension (HbA1c<7.0%) were 419 (39.3%) and 480 (52.1%), respectively. Mean values of body mass index (BMI), diabetic duration and serum creatinine in diabetic patients with hypertension were significantly higher than those in diabetic patients without hypertension (P<0.05). The proportions of macrovascular complications and dyslipidemia in diabetic patients with hypertension were significantly higher than diabetic patients without hypertension (P<0.05). Multiple logistic regression analysis showed that high degree of education, high annual family income and high frequency of glucose monitoring were beneficial factors for glycemic control in diabetic patients with hypertension. Older age, hypertension, higher waist to hip ratio (WHR), the elevated triglyceride and serum creatinine were harmful factors for glycemic control. Conclusions The situation of glycemic control in diabetic patients with hypertension in urban areas of Huai'an is not optimistic. Therefore, community managements of risk factors such as central obesity and increased triglyceride in elder diabetic patients should be strengthened. Key words: Diabetes mellitus, type 2; Hypertension; Risk factors

Achieving glycemic control or reduction of hyperglycemia would significantly decrease most of the complications associated with hyperglycemia in diabetes mellitus. It has been stated that measurement of glycosylated hemoglobin (HbA1C) remains the gold standard for the assessment of glycemic control; there is no consensus whether the Fasting or Postprandial is a better predictor of glycemic control in poor resource setting where HbA1C is not easily accessed or available. The aim of this research is to determine fasting and postprandial plasma glucose and their correlation with HbA1C in glycemic control. A cross sectional case control study was carried out from January, 2023 to July, 2023; a total of 203 participants were recruited into the study. Fasting blood glucose (FBG), 2 hours post prandial blood glucose (2HPBG) were determined in all the subjects using the enzymatic glucose oxidase method for glucose estimation according to the instruction of the manufacturer, while HbA1C was determined using Boroaffinity Chromatographic method according to the instruction of the manufacturer. Statistical data analysis was carried out using SPSS software (Version 25.0, IBM Corp., Armonk, New York USA), and p&lt;0.001 were defined as statistically significant; the correlation between the parameters was carried out using Pearson’s correlation. Both the FBG and the 2HPBG showed positive correlation with HbA1C in the diabetic and control subjects; however, the level of correlation varies. The correlation of FBG and 2HPBG with HbA1C is directly proportional to the concentration of blood glucose level. The FBG for the control and the subjects are 7.40±1.59 and 143.67±5.01, with HbA1C of 4.45±0.05; 6.26±1.47 respectively. The 2HPBG for the control and the subjects are 120.70±1.75 and 192.92±7.05, with HbA1C of 5.56±0.07; 7.82±0.22 respectively. The FBG correlation to HbA1C is r= 0.875, p&lt;0.001; while 2HPBG is r= 0.908, NEWPORT INTERNATIONAL JOURNAL OF PUBLIC HEALTH AND PHARMACY (NIJPP) Volume 4 Issue 2 2023 OPEN ACCESS ©NIJPP ONLINE ISSN: 2992-5479 Publications 2023 PRINT ISSN: 2992-605X Page | 10 p&lt;0.001. The study showed positive correlation of FBG and 2HPBG with HbA1C, since HbA1C is the value of the percentage concentration of glucose at a given period of time; FBG, 2HPBG and HbA1C can be used to evaluate the degree of glycemic control in diabetic patients’ management, in order to minimize or avoid diabetic complications. Keywords: FBG, PBG, Diabetes, HbA1C, Correlation, Complications

Background: Diabetes mellitus is a group of metabolic disorders in which there are high blood glucose levels over a prolonged period. If left untreated, diabetes can cause many complications [13]. Acute complications can include diabetic ketoacidosis, hyperosmolar hyperglycemic state, or death [2]. Serious long-term complications include cardiovascular dis-ease, stroke, chronic kidney disease, foot ulcers, and damage to the eyes [12].Purpose: To study the effect of cupping therapy on glyc-emic control in diabetic patients.Methods: Thirty type 2 diabetic patients were selected from Internal Medicine Department of Central Berket El-Sabaa Hospital to determine the effect of cupping therapy on glycemic control in diabetic patients. The practical work was done in the duration between July 2014 till September 2014.They were diagnosed with specialized physician as T2DM patients, their age ranged from (45-55 years) and they were randomly divided into two groups equal in number. Patients were randomly assigned into two groups (AB each group consisted of fifteen patients. Parameters measured from both groups were HbA1c, fasting plasma glucose, postprandial plasma glucose level. Group (A) performed aerobic training for three sessions every week for 3 months and cupping therapy one time a month for 3 months while group (B) performed aerobic exercise only. Both groups were under medical treatment.Results: There was a significance decrease in HbA1c, fasting blood glucose, and post prandial blood glucose in group A compared with group B post treatment. The percent of improvement of HbA1 c, fasting blood glucose, post prandial plasma glucose for group (A) was 30.13%, 14.08%, and 23.62% and for group (B) was 18.97%, 13.03%, and 16.26% respectively. The significance decrease in the mean values post treatment (p=0.02), (0.04), (0.3).Conclusion: Using cupping therapy combined with aerobic exercise is superior to aerobic exercises only regarding glyc-emic control in type 2 diabetic patients.

Aims: Serine protease inhibitor B1 (SerpinB1) is a neutrophil elastase inhibitor that has been proved to be associated with type 2 diabetes mellitus and pancreatic β-cell proliferation. In this study, we investigated 2 SERPINB1 SNPs, rs114597282 and rs15286, regarding their association with diabetes risk and various anthropometric and biochemical parameters in Egyptian type 2 diabetic patients.Materials and Methods: A total of 160 subjects (62 control and 98 type 2 diabetic patients) participated in this study. Various anthropometric and biochemical parameters were assessed. Genotyping assay for the two SNPs was done using TaqMan genotyping assays. The association of rs15286 variants with risk of diabetes, various biochemical parameters, and glycemic control in diabetic patients was assessed.Results: All genotyped subjects were found to be homozygous TT for SERPINB1 rs114597282. All genotype variants of SERPINB1 rs15286 were found in our Egyptian subjects with A being the minor allele. The SNP rs15286 was not found to be associated with risk of diabetes. The AA genotype was found to be associated with lower fasting plasma glucose, lower HbA1c%, and better β-cell function and glycemic control in diabetic patients. The G allele was associated with poor glycemic control.Conclusions: The genotypes AA, AG, and GG of SERPINB1 gene SNP rs15286 are all represented in the studied sample; however, it is not associated with risk of diabetes. Genotype AA of SNP rs15286 is associated with better glycemic control and better β-cell function in diabetic patients, while the G allele potentially represents the “risk allele” of poor glycemic control.

A number of primary studies suggested that active smoking could be independently associated with incident diabetes. However less is known about the effect of active smoking and smoking cessation on glycemic control in patients with diabetes. The aim of this study was to evaluate the associations of active smoking and smoking cessation with glycemic control in diabetic patients. The present was a cross-sectional study of 10 551 men and 15 297 women with diabetes from the Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal (REACTION) study. Risk factors for glycemic control and the association of active smoking with glycemic control were evaluated using logistic regression models. Poor glycemic control was defined as HbA1c ≥7.0%. Current smokers have an increased risk of poor glycemic control, and the multivariable-adjusted odds ratio (OR) and 95% confidence intervals (CI) of HbA1c ≥7.0% with current smoking were 1.49 (1.35-1.66) in men and 1.56 (1.13-2.15) in women. Further analysis demonstrated a dose-dependent relationship between active smoking and the risk of poor glycemic control in men. Former smokers who quit smoking for <10 years remained at increased risk of poor glycemic control, with the risk leveling off after 10 years of smoking cessation compared with non-smokers, but risk in former smokers was significantly lower than that in current smokers. Active smoking is a modifiable risk factor for poor glycemic control in Chinese diabetic patients.

Serum fructosamine versus glycosylated hemoglobin as an index of glycemic control, hospitalization, and infection in diabetic hemodialysis patients

Short sleep duration has been reported to increase the risk of diabetes. However, the influence of sleep duration on glycemic control in diabetic patients has not been clarified. In this study we evaluated the association between sleep duration and glycemic control in diabetic patients. We analyzed the data from the Korea National Health and Nutrition Examination Survey (KNHANES) 2007-2010. Sleep duration was classified into five groups: <6, 6, 7, 8, and ≥9 h/day. Fasting blood glucose and HbA1c showed a U-shaped trend according to sleep duration. Sleep duration of 7 h/day had the lowest HbA1c (7.26%) among the subjects (P=0.026). In the older age group (≥65 yr), a sleep duration of 6 h/day was associated with the lowest HbA1c (7.26%). The adjusted odds ratio (OR) with a 95% confidence interval (CI) of worse glycemic control (HbA1c ≥7.0%) in group of sleep duration of ≥9 h/day was 1.48 (1.04-2.13) compared with the group of 7 h/day. This relationship disappeared after adjusting duration of diabetes (OR, 1.38; 95% CI, 0.93-2.03). Our results suggest that sleep duration and glycemic control in diabetic patients has U-shaped relationship which was mainly affected by duration of diabetes.

Objective This study was designed to assess hemoglobin A1c (HbA1c) levels in nondiabetic children with end-stage renal disease (ESRD) receiving regular hemodialysis (HD). Background HbA1c level represents an established tool to monitor glycemic control in diabetic patients. Patients and methods We enrolled 30 nondiabetic ESRD children receiving HD as a HD group and 30 healthy children as a control group for this study. All children were subjected to full history taking and physical examination. HbA1c, fasting blood glucose, hemoglobin level, hematocrit value, serum calcium, potassium, phosphate, blood urea nitrogen, creatinine, and parathormone hormone were measured in all participants. HbA1c level was measured by using the turbidimetric immunoassay method. Results We found a statistically significant difference as regards HbA1c (%) between cases and controls. In addition, there was no statistically significant difference in fasting blood glucose (mg/dl) between the two studied groups. Conclusion Our limited data indicate that HbA1c levels are elevated in nondiabetic ESRD patients receiving HD.

Introduction: Limited studies have evaluated the relationship between uric acid and diabetes mellitus (DM), with different studies reporting varying findings. We aimed to investigate the association between levels of uric acid and glycemic control in type 2 DM (T2DM) in our patient cohort. Materials and Methods: We analyzed 200 consecutive patients in the age group of 30–70 years suffering from T2DM with normal renal functions (glomerular filtration rate &gt;60 ml/min/1.73 m2), after excluding patients taking medications for lowering uric acid levels or diuretics. Fasting blood glucose (FBG), random blood glucose (RBG), glycated hemoglobin (HbA1c), and serum uric acid levels were measured in all the patients. Results: The mean age of the study population was 55.25 ± 12.05 years. There was no statistically significant difference in mean age, FBG, RBG, serum uric acid, and HbA1c levels or between males and females in our study cohort. There was a statistically significant negative correlation (P &lt; 0.05) between uric acid levels and HbA1c (r = −0.189) and FBG (r = −0.114). Conclusion: We report an inverse correlation between uric acid levels and glycemic control in diabetic patients with normal renal function, irrespective of gender.

The plasma concentration of 1,5-anhydroglucitol, a new clinical marker of glycemic control in diabetic patients, was evaluated as a marker of glycemia in 83 diabetic and nondiabetic patients with end-stage renal disease. Plasma 1,5-anhydroglucitol concentration decreased and correlated inversely with blood glucose, hemoglobin A1c, or fructosamine in 48 diabetic patients with normal renal function. In 13 nondiabetic patients with end-stage renal disease not on dialysis, plasma 1,5-anhydroglucitol concentrations were lower than in 23 healthy subjects (6.22 +/- 2.10 vs. 24.20 +/- 7.50 micrograms/ml, respectively). The plasma concentration of 1,5-anhydroglucitol concentration in nondiabetic patients with end-stage renal disease was inversely correlated to the urinary N-acetyl-beta-D-glucosaminidase activity (r = -0.634) but not to blood glucose, hemoglobin A1c, or fructosamine. Renal tubular damage may contribute to the low plasma concentration of 1,5-anhydroglucitol in this group. The plasma concentrations of this polyol decreased in both diabetic (4.63 +/- 1.08 micrograms/ml) and nondiabetic patients on hemodialysis (4.71 +/- 0.87 micrograms/ml). In these two groups, there was no correlation between plasma concentration of this polyol and blood glucose, hemoglobin A1c, or fructosamine. The plasma concentration of 1,5-anhydroglucitol decreased after a single hemodialysis session. The results showed that impaired renal function and removal of 1,5-anhydroglucitol by dialysis may contribute to its decreased concentration in patients with end-stage renal disease, but that glycemic control does not. Therefore, we should consider renal function when we use plasma 1,5-anhydroglucitol concentration as a marker of glycemic control in diabetic patients.

The rising prevalence of type 2 diabetes requires increased efforts to find effective therapeutic agents for this complex condition. Following the recent observation that the gut microbiota is altered in diabetic patients, researchers investigated the effect of probiotics in patients with diabetes. The aim of this systematic review was to assess the effects of probiotic consumption on glycemic control in diabetic patients. PubMed, Scopus, Web of Science (formerly ISI Web of Knowledge), Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, and ProQuest Dissertations and Theses databases were searched up to November 2015. Clinical trials in diabetic patients in whom probiotics were administered as an intervention were included. Primary outcomes were fasting blood glucose, insulin concentration, insulin resistance, and hemoglobin A1c. Secondary outcomes were adverse events. Of the 2736 reports that were screened, 13 clinical trials met the inclusion criteria. Pooling data from eligible clinical trials revealed that probiotic supplementation significantly (P < 0.05) decreased fasting blood glucose and hemoglobin A1c in diabetic patients, although the participants' characteristics (eg, body mass index) and the number and type of probiotic microorganisms affected the clinical response. Administration of probiotics appears to have a beneficial role in the management of type 2 diabetes; however, more clinical studies with adequate sample sizes and sound methodology are required to inform the development of evidence-based treatment guidelines.

Low magnesium level as an indicator of poor glycemic control in type 2 diabetic patients with complications

BackgroundIntensive glycemic control is generally recommended for diabetic patients to reduce complications. However, the role of glycemic control in the mortality in diabetic patients with acute myocardial infarction (AMI) remained unclear.MethodsWe selected diabetic patients who measured HbA1c more than 3 times after AMI among 10,719 patients enrolled in the multicenter AMI registry. Patients (n = 1384) were categorized into five groups: according to mean HbA1c level: ≤ 6.5%, > 6.5 to ≤ 7.0%, > 7.0 to ≤ 7.5%, > 7.5 to ≤ 8.0% and > 8.0%. The primary endpoint was all-cause mortality.ResultsDuring a median follow-up of 6.2 years, the patients with a mean HbA1c of 6.5 to 7.0% had the lowest all-cause mortality. Compared to patients with mean HbA1c of 6.5 to 7.0%, the risk of all-cause mortality increased in subjects with mean HbA1c ≤ 6.5% (adjusted hazard ratio [HR] 2.00, 95% confidence interval [CI] 1.02–3.95) and in those with mean HbA1c > 8.0% (adjusted HR 3.35, 95% CI 1.78–6.29). In the subgroup analysis by age, the J-curve relationship between mean HbA1c and all-cause mortality was accentuated in elderly patients (age ≥ 65 years), while there was no difference in all-cause mortality across the HbA1c groups in younger patients (age < 65 years).ConclusionsThe less strict glycemic control in diabetic patients with AMI would be optimal for preventing mortality, especially in elderly patients.

The relation between platelet reactivity and glycemic control in diabetic patients with cardiovascular disease on maintenance aspirin and clopidogrel therapy