Comparison of the therapeutic efficacy between human insulin 30R combined with acarbose and insulin aspart 30 on the postprandial blood glucose in patients with type 2 diabetes

2010 ◽  
Vol 10 (6) ◽  
pp. 443-445
Author(s):  
Jiaoyang ZHENG ◽  
Yongquan SHI ◽  
Xiaoyun FENG ◽  
Zhimin LIU
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Human Insulin ◽  
Insulin Aspart ◽  
Therapeutic Efficacy ◽  
Postprandial Blood Glucose

Gelatinisation and milling whole-wheat increases postprandial blood glucose: randomised crossover study of adults with type 2 diabetes

Diabetologia ◽  
2021 ◽  
Author(s):  
Mona M. Elbalshy ◽  
Andrew N. Reynolds ◽  
Evelyn Mete ◽  
Caleb Robinson ◽  
Indrawati Oey ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Crossover Study ◽  
Postprandial Blood Glucose ◽  
Whole Wheat

scholarly journals Breakfast replacement with a liquid formula improves glycaemic variability in patients with type 2 diabetes: a randomised clinical trial

2019 ◽  
Vol 121 (5) ◽  
pp. 560-566 ◽  
Author(s):  
Jiahui Peng ◽  
Jingyi Lu ◽  
Xiaojing Ma ◽  
Lingwen Ying ◽  
Wei Lu ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Glucose Monitoring ◽  
Mean Amplitude ◽  
Randomised Clinical Trial ◽  
Postprandial Blood Glucose ◽  
Glycaemic Variability ◽  
Intervention Measures ◽  
Before And After

AbstractThere is emerging evidence that glycaemic variability (GV) plays an important role in the development of diabetic complications. The current study aimed to compare the effects of lifestyle intervention (LI) with and without partial meal replacement (MR) on GV. A total of 123 patients with newly diagnosed and untreated type 2 diabetes (T2D) were randomised to receive either LI together with breakfast replacement with a liquid formula (LI+MR) (n 62) or LI alone (n 61) for 4 weeks and completed the study. Each participant was instructed to have three main meals per d and underwent 72-h continuous glucose monitoring (CGM) both before and after intervention. Measures of GV assessed by CGM included the incremental AUC of postprandial blood glucose (AUCpp), standard deviation of blood glucose (SDBG), glucose CV and mean amplitude of glycaemic excursions (MAGE). After a 4-week intervention, the improvements in systolic blood pressure (P=0·046) and time in range (P=0·033) were more pronounced in the LI+MR group than in the LI group. Furthermore, LI+MR caused significantly greater improvements in all GV metrics including SDBG (P=0·005), CV (P=0·002), MAGE (P=0·016) and AUCpp (P<0·001) than did LI. LI+MR (v. LI) was independently associated with improvements in GV after adjustment of covariates (all P<0·05). Our study showed that LI+MR led to significantly greater improvements in GV compared with LI, suggesting that LI+MR could be an effective treatment to alleviate glucose excursions.

scholarly journals The Research of Improved Grey GM (1, 1) Model to Predict the Postprandial Glucose in Type 2 Diabetes

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Yannian Wang ◽  
Fenfen Wei ◽  
Changqing Sun ◽  
Quanzhong Li
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Prediction Model ◽  
Glucose Concentration ◽  
Blood Glucose Concentration ◽  
Original Data ◽  
Postprandial Glucose ◽  
Postprandial Blood Glucose ◽  
Glucose Prediction

Diabetes may result in some complications and increase the risk of many serious health problems. The purpose of clinical treatment is to carefully manage the blood glucose concentration. If the blood glucose concentration is predicted, treatments can be taken in advance to reduce the harm to patients. For this purpose, an improved grey GM (1, 1) model is applied to predict blood glucose with a small amount of data, and especially in terms of improved smoothness it can get higher prediction accuracy. The original data of blood glucose of type 2 diabetes is acquired by CGMS. Then the prediction model is established. Finally, 50 cases of blood glucose from the Henan Province People’s Hospital are predicted in 5, 10, 15, 20, 25, and 30 minutes, respectively, in advance to verify the prediction model. The prediction result of blood glucose is evaluated by the EGA, MSE, and MAE. Particularly, the prediction results of postprandial blood glucose are presented and analyzed. The result shows that the improved grey GM (1, 1) model has excellent performance in postprandial blood glucose prediction.

scholarly journals The Effects of Almonds on Gut Microbiota, Glycometabolism, and Inflammatory Markers in Patients with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomised Controlled Trials

Nutrients ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 3377
Author(s):  
Omorogieva Ojo ◽  
Xiao-Hua Wang ◽  
Osarhumwese Osaretin Ojo ◽  
Amanda Rodrigues Amorim Adegboye
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Gut Microbiota ◽  
Inflammatory Markers ◽  
Meta Analysis ◽  
Fasting Blood Glucose ◽  
Glycated Haemoglobin ◽  
Postprandial Blood Glucose

The use of nutritional interventions for managing diabetes is one of the effective strategies aimed at reducing the global prevalence of the condition, which is on the rise. Almonds are the most consumed tree nut and they are known to be rich sources of protein, monounsaturated fatty acids, essential minerals, and dietary fibre. Therefore, the aim of this review was to evaluate the effects of almonds on gut microbiota, glycometabolism, and inflammatory parameters in patients with type 2 diabetes. Methods: This systematic review and meta-analysis was carried out according to the preferred reporting items for systematic review and meta-analysis (PRISMA). EBSCOhost, which encompasses the Health Sciences Research Databases; Google Scholar; EMBASE; and the reference lists of articles were searched based on population, intervention, control, outcome, and study (PICOS) framework. Searches were carried out from database inception until 1 August 2021 based on medical subject headings (MesH) and synonyms. The meta-analysis was carried out with the Review Manager (RevMan) 5.3 software. Results: Nine randomised studies were included in the systematic review and eight were used for the meta-analysis. The results would suggest that almond-based diets have significant effects in promoting the growth of short-chain fatty acid (SCFA)-producing gut microbiota. Furthermore, the meta-analysis showed that almond-based diets were effective in significantly lowering (p < 0.05) glycated haemoglobin (HbA1c) levels and body mass index (BMI) in patients with type 2 diabetes. However, it was also found that the effects of almonds were not significant (p > 0.05) in relation to fasting blood glucose, 2 h postprandial blood glucose, inflammatory markers (C-reactive protein and Tumour necrosis factor α, TNF-α), glucagon-like peptide-1 (GLP-1), homeostatic model assessment of insulin resistance (HOMA–IR), and fasting insulin. The biological mechanisms responsible for the outcomes observed in this review in relation to reduction in HbA1c and BMI may be based on the nutrient composition of almonds and the biological effects, including the high fibre content and the low glycaemic index profile. Conclusion: The findings of this systematic review and meta-analysis have shown that almond-based diets may be effective in promoting short-chain fatty acid-producing bacteria and lowering glycated haemoglobin and body mass index in patients with type 2 diabetes compared with control. However, the effects of almonds were not significant (p > 0.05) with respect to fasting blood glucose, 2 h postprandial blood glucose, inflammatory markers (C-reactive protein and TNF-α), GLP-1, HOMA–IR, and fasting insulin.

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