Preliminary study of the effects of Tai Chi and Qigong medical exercise on indicators of metabolic syndrome and glycaemic control in adults with raised blood glucose levels

2008 ◽  
Vol 43 (11) ◽  
pp. 840-844 ◽  
Author(s):  
X. Liu ◽  
Y. D. Miller ◽  
N. W. Burton ◽  
W. J. Brown
Keyword(s):  
Metabolic Syndrome ◽  
Blood Glucose ◽  
Glycaemic Control ◽  
Tai Chi ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Preliminary Study

Online Prediction of Blood Glucose Levels using Genetic Algorithm

2014 ◽  
pp. 299-310
Author(s):  
Khaled Eskaf ◽  
Tim Ritchings ◽  
Osama Bedawy
Keyword(s):  
Blood Glucose ◽  
Glucose Monitoring ◽  
Simulation Software ◽  
Machine Learning Techniques ◽  
Diabetic Patients ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Learning Techniques ◽  
Preliminary Study ◽  
Online Prediction

Diabetes mellitus is one of the most common chronic diseases. The number of cases of diabetes in the world is likely to increase more than two fold in the next 30 years: from 115 million in 2000 to 284 million in 2030. This chapter is concerned with helping diabetic patients to manage themselves by developing a computer system that predicts their Blood Glucose Level (BGL) after 30 minutes on the basis of their current levels, so that they can administer insulin. This will enable the diabetic patient to continue living a normal daily life, as much as is possible. The prediction of BGLs based on the current levels BGLs become feasible through the advent of Continuous Glucose Monitoring (CGM) systems, which are able to sample patients' BGLs, typically 5 minutes, and computer systems that can process and analyse these samples. The approach taken in this chapter uses machine-learning techniques, specifically Genetic Algorithms (GA), to learn BGL patterns over an hour and the resulting value 30 minutes later, without questioning the patients about their food intake and activities. The GAs were invested using the raw BGLs as input and metadata derived from a Diabetic Dynamic Model of BGLs supplemented by the changes in patients' BGLs over the previous hour. The results obtained in a preliminary study including 4 virtual patients taken from the AIDA diabetes simulation software and 3 volunteers using the DexCom SEVEN system, show that the metadata approach gives more accurate predictions. Online learning, whereby new BGL patterns were incorporated into the prediction system as they were encountered, improved the results further.

Knowledge of Diabetes mellitus and Glycaemic Control

1997 ◽  
Vol 6 (4) ◽  
pp. 186-197
Author(s):  
David L. Robinson ◽  
Mahmoud Al-Bustan ◽  
Milad S. Bitar ◽  
Adnan Al-Asousi ◽  
Sobia Majeed
Keyword(s):  
Diabetes Mellitus ◽  
Blood Glucose ◽  
Glycaemic Control ◽  
Hospital Admissions ◽  
Factor Model ◽  
Fasting Blood Glucose ◽  
General Factor ◽  
Diabetes Knowledge ◽  
Glucose Levels ◽  
Blood Glucose Levels

It has been claimed that lack of knowledge of diabetes mellitus has been a cause of excess admissions and morbidity. There is also some evidence that diabetic education programs can improve self-regulatory behaviour and reduce hospital admissions. In this report we test the hypothesis that greater knowledge of diabetes should be associated with better glycaemic control and lower fasting blood glucose levels. Responses to diabetes knowledge questions were provided by 420 patients attending diabetic clinics in Kuwait. In an earlier and complementary report a principal components analysis revealed that knowledge of diabetes cannot be understood in terms of a single general factor. With a subsequent Varimax rotation we obtained 12 uncorrelated knowledge factors with eigenvalues greater than unity and these would all be confounded in the simple aggregation of correct answers to diabetes knowledge questions employed in earlier studies. Results are now described which show that the 12-factor model of diabetes knowledge is better able to predict blood glucose levels than the scores obtained on a single scale by just summing the correct answers to all diabetes knowledge questions. A standard multiple linear regression with the diabetes knowledge factors age, sex and ‘years since diagnosis’ as independent variables, and fasting blood glucose levels as the dependent variable, shows that 4 of the 12 factors yield statistically significant semi-partial correlation coefficients that account for unique fractions of the total variance of blood glucose levels. The meaning of these 4 factors is discussed with special reference to glycaemic control and blood glucose levels.

scholarly journals Sample of Aboriginal Australians, 2-hour post-load insulin concentrations are greatest between fasting plasma glucose values of 6.7-7.3 mmol/l

2018 ◽  
Vol 1 (2) ◽  
pp. 01-05
Author(s):  
Paul Aveyard
Keyword(s):  
Blood Glucose ◽  
Glycaemic Control ◽  
Routine Care ◽  
Systematic Sampling ◽  
Control Group ◽  
Diabetic Patients ◽  
Glucose Levels ◽  
Good Glycaemic Control ◽  
Blood Glucose Levels ◽  
The Impact

Background: Prevention of diabetic complications requires good glycaemic control. This study aimed to provide type 2 diabetes patients with remote active care and glycaemic control through the use of videophone technology without the need for them to attend hospital. The literature recommends additional research to study the impact of technical innovations on improved disease self-management and medical outcome. This is the only study to be conducted in Turkey concerning patient monitoring using videophone technology. The aim of the study was to establish the effectiveness of the use of videophone technology in the glycaemic control of patients with diabetes living in remote areas. Methods: This is a prospective, randomized control study using the systematic sampling method (using half ratio), in which 24 patients were chosen for the Experimental Group (EG) and another 24 for the Control Group (CG). All of the patients agreed to participate in the study. Patients in the CG received routine care, while the glycaemic control and consultations for patients in the EG were conducted using videophone technology. The patients were monitored by videophone for a total of 6 months. The HbA1c and blood glucose values recorded over the 6 month monitoring period were analyzed to determine the effectiveness of using a videophone. Results: The mean age of the individuals in the EG was 54.41 ± 8.54 years (Min=43 Max=78) and in the CG it was 57.25 ± 9.61 (Min=40 Max=77). In both groups, 50% of the individuals were men and 50% were women. When the two groups were compared, it was was found that the preprandial blood glucose levels of the diabetic patients in the EG (mean 159.48 ± 40.71mg/dl) were lower by 13.55 ± 52.89 mg / dl than the preprandial blood glucose levels of the diabetic patients in the CG (mean 173.03 ± 65.07 mg/dl). It was determined at the end of the six-month monitoring that the A1c levels of the individuals in the EG were significinatly lowered by 0.49% in total, and that the A1c levels of the individuals in the CG were higher by 0.17 % in total. Conclusions: It was shown that videophone technology can be useful in the glycaemic control of diabetic patients in Turkey.

scholarly journals The use of low-glycaemic index diets in diabetes control

2010 ◽  
Vol 104 (6) ◽  
pp. 797-802 ◽  
Author(s):  
D. E. Thomas ◽  
E. J. Elliott
Keyword(s):  
Blood Glucose ◽  
Glycaemic Control ◽  
Diabetes Management ◽  
Weighted Mean Difference ◽  
Blood Glucose Control ◽  
Glycaemic Index ◽  
Cochrane Library ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Improved Glycaemic Control

The aim of diabetes management is to normalise blood glucose levels since improved blood glucose control is associated with fewer complications. Food affects blood glucose levels; however, there is no universal approach to the optimal diabetic diet and there is controversy about the usefulness of the low-glycaemic index (GI) diet. To assess the effects of low-GI diets on glycaemic control in diabetes, we conducted electronic searches of the Cochrane Library, MEDLINE, EMBASE and CINAHL. We assessed randomised controlled trials (RCT) with interventions >4 weeks that compared a low-GI diet with a higher-GI diet for type 1 or type 2 diabetes. Twelve RCT (n612) were identified. There was a significant decrease in glycated Hb (HbA1c) with low-GI diet than with the control diet, indicating improved glycaemic control (seven trials,n457, weighted mean difference (WMD) − 0·4 % HbA1c, 95 % CI − 0·7, − 0·20,P = 0·001). In four studies reporting the results for glycaemic control as fructosamine, three of which were 6 weeks or less in duration, pooled data showed a decrease in fructosamine (WMD − 0·23 mmol/l, 95 % CI − 0·47, 0·00,P = 0·05),n141, with low-GI diet than with high-GI diet. Glycosylated albumin levels decreased significantly with low-GI diet, but not with high-GI diet, in one study that reported this outcome. Lowering the GI of the diet may contribute to improved glycaemic control in diabetes.

scholarly journals Verification of the Impact of Blood Glucose Level on Liver Carcinogenesis and the Efficacy of a Dietary Intervention in a Spontaneous Metabolic Syndrome Model

2021 ◽  
Vol 22 (23) ◽  
pp. 12844
Author(s):  
Mayuko Ichimura-Shimizu ◽  
Takeshi Kageyama ◽  
Takeshi Oya ◽  
Hirohisa Ogawa ◽  
Minoru Matsumoto ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Liver Tumors ◽  
Liver Carcinogenesis ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Urinary Glucose ◽  
The Impact

Metabolic syndrome (MS) is a risk factor for type 2 diabetes mellitus, vascular inflammation, atherosclerosis, and renal, liver, and heart diseases. Non-alcoholic steatohepatitis (NASH) is a progressive representative liver disease and may lead to the irreversible calamities of cirrhosis and hepatocellular carcinoma. Metabolic disorders such as hyperglycemia have been broadly reported to be related to hepatocarcinogenesis in NASH; however, direct evidence of a link between hyperglycemia and carcinogenesis is still lacking. Tsumura Suzuki Obese Diabetic (TSOD) mice spontaneously develop metabolic syndrome, including obesity, insulin resistance, and NASH-like liver phenotype, and eventually develop hepatocellular carcinomas. TSOD mice provide a spontaneous human MS-like model, even with significant individual variations. In this study, we monitored mice in terms of their changes in blood glucose levels, body weights, and pancreatic and liver lesions over time. As a result, liver carcinogenesis was delayed in non-hyperglycemic TSOD mice compared to hyperglycemic mice. Moreover, at the termination point of 40 weeks, liver tumors appeared in 18 of 24 (75%) hyperglycemic TSOD mice; in contrast, they only appeared in 5 of 24 (20.8%) non-hyperglycemic mice. Next, we investigated three kinds of oligosaccharide that could lower blood glucose levels in hyperglycemic TSOD mice. We monitored the levels of blood and urinary glucose and assessed pancreatic lesions among the experimental groups. As expected, significantly lower levels of blood and urinary glucose and smaller deletions of Langerhans cells were found in TSOD mice fed with milk-derived oligosaccharides (galactooligosaccharides and lactosucrose). At the age of 24 weeks, mild steatohepatitis was found in the liver but there was no evidence of liver carcinogenesis. Steatosis in the liver was alleviated in the milk-derived oligosaccharide-administered group. Taken together, suppressing the increase in blood glucose level from a young age prevented susceptible individuals from diabetes and the onset of NAFLD/NASH, as well as carcinogenesis. Milk-derived oligosaccharides showed a lowering effect on blood glucose levels, which may be expected to prevent liver carcinogenesis.

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