The effect of Tai Chi on health related quality of life in people with elevated blood glucose or diabetes : a randomized controlled trial

Purpose The aim was to assess the effects of a Tai Chi based program on health related quality of life (HR-QOL) in people with elevated blood glucose or diabetes who were not on medication for glucose control. Method 41 participants were randomly allocated to either a Tai Chi intervention group (N = 20) or a usual medical care control group (N = 21). The Tai Chi group involved 3 x 1.5 hour supervised and group-based training sessions per week for 12 weeks. Indicators of HR-QOL were assessed by self-report survey immediately prior to and after the intervention. Results There were significant improvements in favour of the Tai Chi group for the SF36 subscales of physical functioning (mean difference = 5.46, 95% CI = 1.35-9.57, P < 0.05), role physical (mean difference = 18.60, 95% CI = 2.16-35.05, P < 0.05), bodily pain (mean difference = 9.88, 95%CI = 2.06-17.69, P < 0.05) and vitality (mean difference = 9.96, 95% CI = 0.77-19.15, P < 0.05). Conclusions The findings show that this Tai Chi program improved indicators of HR-QOL including physical functioning, role physical, bodily pain and vitality in people with elevated blood glucose or diabetes who were not on diabetes medication.

A preliminary study of the effects of Tai Chi and Qigong medical exercise on indicators of metabolic syndrome, glycaemic control, health-related quality of life, and psychological health in adults with elevated blood glucose

Objectives To evaluate the feasibility, acceptability and effects of a Tai Chi and Qigong exercise programme in adults with elevated blood glucose. Design, Setting, and Participants A single group pre–post feasibility trial with 11 participants (3 male and 8 female; aged 42–65 years) with elevated blood glucose. Intervention Participants attended Tai Chi and Qigong exercise training for 1 to 1.5 h, 3 times per week for 12 weeks, and were encouraged to practise the exercises at home. Main Outcome Measures Indicators of metabolic syndrome (body mass index (BMI), waist circumference, blood pressure, fasting blood glucose, triglycerides, HDL-cholesterol); glucose control (HbA1c, fasting insulin and insulin resistance (HOMA)); health-related quality of life; stress and depressive symptoms. Results There was good adherence and high acceptability. There were significant improvements in four of the seven indicators of metabolic syndrome including BMI (mean difference −1.05, p<0.001), waist circumference (−2.80 cm, p<0.05), and systolic (−11.64 mm Hg, p<0.01) and diastolic blood pressure (−9.73 mm Hg, p<0.001), as well as in HbA1c (−0.32%, p<0.01), insulin resistance (−0.53, p<0.05), stress (−2.27, p<0.05), depressive symptoms (−3.60, p<0.05), and the SF-36 mental health summary score (5.13, p<0.05) and subscales for general health (19.00, p<0.01), mental health (10.55, p<0.01) and vitality (23.18, p<0.05). Conclusions The programme was feasible and acceptable and participants showed improvements in metabolic and psychological variables. A larger controlled trial is now needed to confirm these promising preliminary results.

Air pollution and fasting blood glucose: A longitudinal study in China

Limited studies have examined the associations between air pollutants [particles with diameters of 10um or less (PM10), sulfur dioxide (SO2), and nitrogen dioxide (NO2)] and fasting blood glucose (FBG). We collected data for 27,685 participants who were followed during 2006 and 2008. Generalized Estimating Equation models were used to examine the effects of air pollutants on FBG while controlling for potential confounders. We found that increased exposure to NO2, SO2 and PM10 was significantly associated with increased FBG levels in single pollutant models (p<0.001). For exposure to 4 days’ average of concentrations, a 100 µg/m3 increase in SO2, NO2, and PM10 was associated with 0.17 mmol/L (95%CI: 0.15–0.19), 0.53 mmol/L (95%CI: 0.42–0.65), and 0.11 mmol/L (95%CI: 0.07–0.15) increase in FBG, respectively. In the multi-pollutant models, the effects of SO2 were enhanced, while the effects of NO2 and PM10 were alleviated. The effects of air pollutants on FBG were stronger in female, elderly, and overweight people than in male, young and underweight people. In conclusion, the findings suggest that air pollution increases the levels of FBG. Vulnerable people should pay more attention on highly polluted days to prevent air pollution-related health issues.

The effect of blood glucose on the vasculature in young patients with type 1 diabetes

Background. Patients with type 1 diabetes are at markedly increased risk of vascular complications. In this respect it is noteworthy that hyperglycaemia that is shown to cause endothelial dysfunction, has clearly been shown to be a risk factor for diabetic microvascular disease. However, the role of hyperglycaemia as a predictor of macrovascular disease is not as clear as for microvascular disease, although type 1 diabetes itself increases the risk of cardiovascular disease substantially. Furthermore, it is not known whether it is the short-term or the long-term hyperglycaemia that confers possible risk. In addition, the role of glucose variability as a predictor of complications is to a large extent unexplored. Interestingly, although hyperglycaemia increases the risk of pre-eclampsia in women with type 1 diabetes, it is unclear whether pre-eclampsia, a condition characterized by endothelial dysfunction, is also a risk factor for microvascular complication, diabetic nephropathy. Aims. This doctoral thesis investigated the role of acute hyperglycaemia and glucose variability on arterial stiffness and cardiac ventricular repolarisation in male patients with type 1 diabetes as well as in healthy male volunteers. The thesis also explored whether acute hyperglycaemia leads to an inflammatory response, endothelial dysfunction and oxidative stress. Finally, the role of pre-eclampsia, as a predictor of diabetic nephropathy in type 1 diabetes was examined. Subjects and methods. In order to study glucose variability and the daily glycaemic control, 22 male patients with type 1 diabetes, without any diabetic complications, were monitored for 72-h with a continuous glucose monitoring system. At the end of the 72-h glucose monitoring period a 2-h hyperglycaemic clamp was performed both in the patients with type 1 diabetes and in the 13 healthy age-matched male volunteers. Blood pressure, arterial stiffness and QT time were measured to detect vascular changes during acute hyperglycaemia. Blood samples were drawn at baseline (normoglycaemia) and during acute hyperglycaemia. In another patient sample, women with type 1 diabetes were followed during their pregnancy and restudied eleven years later to elucidate the role of pre-eclampsia and pregnancy-induced hypertension as potential risk factors for diabetic nephropathy. Results and conclusions. Acute hyperglycaemia increased arterial stiffness as well as caused a disturbance in the myocardial ventricular repolarisation, emphasizing the importance of a strict daily glycaemic control in male patients with type 1 diabetes. An inflammatory response was also observed during acute hyperglycaemia. Furthermore, a high mean daily blood glucose but not glucose variability per se is associated with arterial stiffness. While glucose variability in turn correlated with central blood pressure, the results suggest that the glucose metabolism is closely linked to the haemodynamic changes in male patients with uncomplicated type 1 diabetes. Notably, the results are not directly applicable to females. Finally, a history of a pre-eclamptic pregnancy, but not pregnancy-induced hypertension was associated with increased risk of diabetic nephropathy.

Optimal Blood Glucose Regulation using Single Network Adaptive Critics

Diabetes is a serious disease during which the body's production and use of insulin is impaired, causing glucose concentration level toincrease in the bloodstream. Regulating blood glucose levels as close to normal as possible, leads to a substantial decrease in long term complications of diabetes. In this paper, an intelligent neural network on-line optimal feedback treatment strategy based on nonlinear optimal control theory is presented for the disease using subcutaneous treatment strategy. A simple mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system is considered based on the Bergman's minimal model. A glucose infusion term representing the effect of glucose intake resulting from a meal is introduced into the model equations. The efficiency of the proposed controllers is shown taking random parameters and random initial conditions in presence of physical disturbances like food intake. A comparison study with linear quadratic regulator theory brings Out the advantages of the nonlinear control synthesis approach. Simulation results show that unlike linear optimal control, the proposed on-line continuous infusion strategy never leads to severe hypoglycemia problems.

Optimal blood glucose regulation of diabetic patients using single network adaptive critics

Diabetes is a long-term disease during which the body's production and use of insulin are impaired, causing glucose concentration level to increase in the bloodstream. Regulating blood glucose levels as close to normal as possible leads to a substantial decrease in long-term complications of diabetes. In this paper, an intelligent online feedback-treatment strategy is presented for the control of blood glucose levels in diabetic patients using single network adaptive critic (SNAC) neural networks (which is based on nonlinear optimal control theory). A recently developed mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system has been revised and considered for synthesizing the neural network for feedback control. The idea is to replicate the function of pancreatic insulin, i.e. to have a fairly continuous measurement of blood glucose and a situation-dependent insulin injection to the body using an external device. Detailed studies are carried out to analyze the effectiveness of this adaptive critic-based feedback medication strategy. A comparison study with linear quadratic regulator (LQR) theory shows that the proposed nonlinear approach offers some important advantages such as quicker response, avoidance of hypoglycemia problems, etc. Robustness of the proposed approach is also demonstrated from a large number of simulations considering random initial conditions and parametric uncertainties. Copyright (C) 2009 John Wiley & Sons, Ltd.

Studies on Carbon Mediated Paste Screen Printed Sensors for Blood Glucose Sensing Application

Ready-to-use screen printed glucose sensors are fabricated using Prussian Blue (PB) and Cobalt Phthalocyanine (CoPC) mediated carbon inks as working electrodes. The reference and counter electrodes are screen printed using silver/silver chloride and graphitic carbon paste respectively. The screen printed reference electrodes (internal reference electrode (IRE)) are found to be stable for more than 60 minutes when examined with saturated calomel electrode. Optimal operating voltage for PB and CoPC screen printed sensors are determined by hydrodynamic voltammetric technique. Glucose oxidase is immobilized on the working electrodes by cross-linking method. PB mediated glucose sensor exhibits a sensitivity of 5.60 mA cm(-2)/mM for the range, 10 to 1000 mu M. Sensitivity of CoPC mediated glucose sensor is found to be 5.224 mu A cm(-2)/mM and amperometeric response is linear for the range, 100 to 1500 mu M. Interference studies on the fabricated glucose sensors are conducted with species like uric acid and ascorbic acid. PB mediated sensors showed a completely interference-free behavior. The sensing characteristics of PB mediated glucose sensors are also studied in diluted human serum samples and the results are compared with the values obtained through standard clinical method. The co-efficient of variation is found to be less than 5%. (C) 2015 The Electrochemical Society. All rights reserved.

Preprandial versus postprandial blood glucose monitoring in type 1 diabetic pregnancy: A randomized controlled clinical trial

OBJECTIVE: This study was undertaken to compare preprandial and postprandial capillary glucose monitoring in pregnant women with type 1 diabetes.

Is the formula of Traub still up to date in antemortem blood glucose level estimation?

According to the hypothesis of Traub, also known as the 'formula of Traub', postmortem values of glucose and lactate found in the cerebrospinal fluid or vitreous humor are considered indicators of antemortem blood glucose levels. However, because the lactate concentration increases in the vitreous and cerebrospinal fluid after death, some authors postulated that using the sum value to estimate antemortem blood glucose levels could lead to an overestimation of the cases of glucose metabolic disorders with fatal outcomes, such as diabetic ketoacidosis. The aim of our study, performed on 470 consecutive forensic cases, was to ascertain the advantages of the sum value to estimate antemortem blood glucose concentrations and, consequently, to rule out fatal diabetic ketoacidosis as the cause of death. Other biochemical parameters, such as blood 3-beta-hydroxybutyrate, acetoacetate, acetone, glycated haemoglobin and urine glucose levels, were also determined. In addition, postmortem native CT scan, autopsy, histology, neuropathology and toxicology were performed to confirm diabetic ketoacidosis as the cause of death. According to our results, the sum value does not add any further information for the estimation of antemortem blood glucose concentration. The vitreous glucose concentration appears to be the most reliable marker to estimate antemortem hyperglycaemia and, along with the determination of other biochemical markers (such as blood acetone and 3-beta-hydroxybutyrate, urine glucose and glycated haemoglobin), to confirm diabetic ketoacidosis as the cause of death.

A Gain Scheduling Model Predictive Controller for Blood Glucose Control in Type 1 Diabetes

This paper presents a control strategy for blood glucose(BG) level regulation in type 1 diabetic patients. To design the controller, model-based predictive control scheme has been applied to a newly developed diabetic patient model. The controller is provided with a feedforward loop to improve meal compensation, a gain-scheduling scheme to account for different BG levels, and an asymmetric cost function to reduce hypoglycemic risk. A simulation environment that has been approved for testing of artificial pancreas control algorithms has been used to test the controller. The simulation results show a good controller performance in fasting conditions and meal disturbance rejection, and robustness against model–patient mismatch and errors in meal estimation

Prediction of postprandial blood glucose under intra-patient variability and uncertainty and its use in the design of insulin dosing strategies for type 1 diabetic patients

In this thesis I propose a novel method to estimate the dose and injection-to-meal time for low-risk intensive insulin therapy. This dosage-aid system uses an optimization algorithm to determine the insulin dose and injection-to-meal time that minimizes the risk of postprandial hyper- and hypoglycaemia in type 1 diabetic patients. To this end, the algorithm applies a methodology that quantifies the risk of experiencing different grades of hypo- or hyperglycaemia in the postprandial state induced by insulin therapy according to an individual patient’s parameters. This methodology is based on modal interval analysis (MIA). Applying MIA, the postprandial glucose level is predicted with consideration of intra-patient variability and other sources of uncertainty. A worst-case approach is then used to calculate the risk index. In this way, a safer prediction of possible hyper- and hypoglycaemic episodes induced by the insulin therapy tested can be calculated in terms of these uncertainties.

Optimal H∞ insulin injection control for blood glucose regulation in diabetic patients

The theory of H/sup /spl infin// optimal control has the feature of minimizing the worst-case gain of an unknown disturbance input. When appropriately modified, the theory can be used to design a "switching" controller that can be applied to insulin injection for blood glucose (BG) regulation. The "switching" controller is defined by a collection of basic insulin rates and a rule that switches the insulin rates from one value to another. The rule employed an estimation of BG from noisy measurements, and the subsequent optimization of a performance index that involves the solution of a "jump" Riccati differential equation and a discrete-time dynamic programming equation. With an appropriate patient model, simulation studies have shown that the controller could correct BG deviation using clinically acceptable insulin delivery rates.