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 Blood Glucose Fluctuations in Type 2 Diabetes Patients Treated with Multiple Daily Injections

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Feng-fei Li ◽  
Li-yuan Fu ◽  
Wen-li Zhang ◽  
Xiao-fei Su ◽  
Jin-dan Wu ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Treatment Group ◽  
Intensive Therapy ◽  
Glucose Monitoring ◽  
Mean Amplitude ◽  
Newly Diagnosed ◽  
Glucose Fluctuations ◽  
Diabetes Patients

To compare blood glucose fluctuations in type 2 diabetes mellitus (T2DM) patients were treated using three procedures: insulin intensive therapy which is continuous subcutaneous insulin infusion (CSII), MDI3 (three injections daily), and MDI4 (four injections daily). T2DM patients were hospitalized and were randomly assigned to CSII, aspart 30-based MDI3, and glargine based MDI4. Treatments were maintained for 2-3 weeks after the glycaemic target was reached. After completing the baseline assessment, 6-day continuous glucose monitoring (CGM) was performed before and after completion of insulin treatment. Treatment with CSII provided a greater improvement of blood glucose fluctuations than MDI (MDI3 or MDI4) therapy either in newly diagnosed or in long-standing T2DM patients. In long-standing diabetes patients, the MDI4 treatment group had significantly greater improvement of mean amplitude glycemic excursion (MAGE) than the MDI3 treatment group. However, in patients with newly diagnosed diabetes, there were no significant differences in the improvement of MAGE between MDI3 and MDI4 groups. Glargine based MDI4 therapy provided better glucose fluctuations than aspart 30-based MDI3 therapy, especially in long-standing T2DM patients, if CSII therapy was not available.

scholarly journals Evaluating Glycemic Control During Basalin or Lantus Administration in Adults With Controlled Type 2 Diabetes Mellitus Using Continuous Glucose Monitoring

2021 ◽  
Vol 12 ◽  
Author(s):  
Huiying Wang ◽  
Yunting Zhou ◽  
Xiaofang Zhai ◽  
Bo Ding ◽  
Ting Jing ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Area Under The Curve ◽  
Mean Amplitude

AimThis study aims at evaluating glycemic control during Basalin or Lantus administration in adults with controlled type 2 diabetes mellitus using continuous glucose monitoring system (CGM).Methods47 patients with well-controlled T2DM using both Basalin and oral hypoglycemic drugs were recruited. CGM were applied from day 1 to day 3 with the unchanged dose of Basalin and then removed from day 4. A washout was performed with Lantus at the same dose as Basalin from day 4 to day 10. Then patients were continued to install the CGM under Lantus administration from day 11 to day 13. Variables of CGM, such as the area under the curve (AUC) for both hyperglycemia and hypoglycemia, 24h mean blood glucose (24h MBG), 24h standard deviation of blood glucose (24h SDBG), 24h mean amplitude of glycemic excursion (24h MAGE), PT (percentage of time), and time in range (TIR), were calculated and compared between Basalin group and Lantus group.ResultsThe group of Lantus showed lower 24h MBG (p&lt;0.01), 24h MAGE (p&lt;0.05), and lower 24h SDBG (p&lt;0.01) than the Basalin group. Lantus−treated patients had a lower PT and AUC when the cut-off point for blood glucose was 10 mmol/L (p&lt;0.05) and 13.9 mmol/L (p&lt;0.05), respectively. In this study, no patient developed symptomatic hypoglycemia, few hypoglycemia was observed and there was no difference of hypoglycemia between the two groups.ConclusionIn patients with well-controlled T2DM who were treated with insulin glargine, Lantus group showed lower MBG, GV, and lower PT (BG &gt; 10.0 mmol/L, BG &gt; 13.9 mmol/L) than Basalin group. In summary, for T2DM population with HbA1c ≤ 7%, Lantus may be a better choice compared with Basalin.

941-P: Frequency of Blood Glucose Monitoring in Relation to Medical Cost and Glycemic Control in Hospitalized Patients with Type 2 Diabetes

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 941-P
Author(s):  
LEI ZHANG ◽  
YAN GU ◽  
YUXIU YANG ◽  
NA WANG ◽  
WEIGUO GAO ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Medical Cost ◽  
Glucose Monitoring ◽  
Hospitalized Patients ◽  
Blood Glucose Monitoring

scholarly journals Real-time continuous glucose monitoring versus self-monitoring of blood glucose in adults with insulin-treated type 2 diabetes: a protocol for a randomised controlled single-centre trial

BMJ Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. e040648
Author(s):  
Nanna Lind ◽  
Dorte Lindqvist Hansen ◽  
Signe Sætre Rasmussen ◽  
Kirsten Nørgaard
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Peer Support ◽  
Continuous Glucose Monitoring ◽  
Data Protection ◽  
Treatment Options ◽  
Glucose Monitoring ◽  
Single Centre ◽  
Self Monitoring

IntroductionMedical treatment options for type 2 diabetes (T2D) have increased over the last decade and enhance the possibility of individualised treatment strategies where insulin is still one of them. In spite of the advancements in treatment options, less than one-third of the population with T2D obtain their optimal glycaemic goal. In persons with type 1 diabetes, continuous glucose monitoring (CGM) has shown to be the most important driver for improvement in glycaemic control, even more than insulin-pump therapy. The use of technology in T2D has only been investigated in few studies.The overall objective of the research study is to examine the effectiveness of the use of CGM versus self-monitoring of blood glucose (SMBG) in persons with insulin-treated T2D on glycaemic variables and patient-reported outcomes on treatment satisfaction, health behaviour and well-being. The independent effect of peer support will also be studied.Methods and analysisThe study is a single centre, prospective, randomised, open-labelled, three-armed study with the randomisation 2:1:2 in group A with CGM, group B with CGM and peer support, and group C as a control group with SMBG. The participants receive a training course unique for the allocation group. The study runs for 12 months and includes 100 adult participants with insulin-treated T2D, treated at the outpatient clinic at Steno Diabetes Center Copenhagen. Primary outcome is difference in change in time in range. Recruitment begins in August 2020 and ends in July 2021. Final 12-month follow-up is anticipated to be in August 2022.Ethics and disseminationThe study will be carried out in accordance with the Helsinki Declaration and is approved by the Scientific Ethics Committee of the Capital Region (H-20000843). Data collection and handling will be performed in accordance with the General Data Protection Regulation and is approved by the Danish Data Protection Agency (J-2020-100). Dissemination will be in international peer-reviewed journals, conferences and a plain-language summary for participants.Trial registration numberClinicalTrials.gov Registry (NCT04331444).Protocol versionV.3, 11 December 2020.

scholarly journals Glycemic variability and cardiovascular disease in patients with type 2 diabetes

2021 ◽  
Vol 9 (1) ◽  
pp. e002032
Author(s):  
Marcela Martinez ◽  
Jimena Santamarina ◽  
Adrian Pavesi ◽  
Carla Musso ◽  
Guillermo E Umpierrez
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Glycated Hemoglobin ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Cardiovascular Complications ◽  
Glucose Levels ◽  
Increased Risk ◽  
Patients With Diabetes

Glycated hemoglobin is currently the gold standard for assessment of long-term glycemic control and response to medical treatment in patients with diabetes. Glycated hemoglobin, however, does not address fluctuations in blood glucose. Glycemic variability (GV) refers to fluctuations in blood glucose levels. Recent clinical data indicate that GV is associated with increased risk of hypoglycemia, microvascular and macrovascular complications, and mortality in patients with diabetes, independently of glycated hemoglobin level. The use of continuous glucose monitoring devices has markedly improved the assessment of GV in clinical practice and facilitated the assessment of GV as well as hypoglycemia and hyperglycemia events in patients with diabetes. We review current concepts on the definition and assessment of GV and its association with cardiovascular complications in patients with type 2 diabetes.

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 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.

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