Fibrates in the prevention of cardiovascular disease in patients with type 2 diabetes mellitus: meta-analysis of randomised controlled trials

To assess the impact of lipid lowering treatment with fibrates on cardiovascular endpoints in patients with type 2 diabetes mellitus.

Differential effect of pioglitazone (PGZ) and rosiglitazone (RGZ) on postprandial glucose and lipid metabolism in patients with type 2 diabetes mellitus: a prospective, randomized crossover study

Postprandial metabolism is impaired in patients with type 2 diabetes (T2Dm). Two thiazolidinediones pioglitazone (PGZ) and rosiglitazone (RGZ) have similar effects on glycaemic control but differ in their effects on fasting lipids. This study investigated the effects of RGZ and PGZ on postprandial metabolism in a prospective, randomized crossover trial.

Effects of alcohol consumption on mortality in patients with Type 2 diabetes mellitus

Moderate alcohol intake has been associated with increased life expectancy due to reduced mortality from cardiovascular disease. We prospectively examined the effects of alcohol consumption on mortality in Type 2 diabetic patients in Switzerland.

[Treatment of hypertension in type 2 diabetes mellitus--2002 update]

Arterial hypertension and diabetes are potent independent risk factors for cardiovascular, cerebral, renal and peripheral (atherosclerotic) vascular disease. The prevalence of hypertension in diabetic individuals is approximately twice that in the non-diabetic population. Diabetic individuals with hypertension have a greater risk of macrovascular and microvascular disease than normotensive diabetic individuals. Hypertension is a major contributor to morbidity and mortality in diabetes, and should be recognized and treated early. Type 2 diabetes and hypertension share certain risk factors such as overweight, visceral obesity, and possibly insulin resistance. Life-style modifications (weight reduction, exercise, limitation of daily alcohol intake, stop smoking) are the foundation of hypertension and diabetes management as the definitive treatment or adjunctive to pharmacological therapy. Additional pharmacological therapy should be initiated when life-style modifications are unsuccessful or hypertension is too severe at the time of diagnosis. All classes of antihypertensive drugs are effective in controlling blood pressure in diabetic patients. For single-agent therapy, ACE-inhibitors, angiotensin receptor blocker, beta-blockers, and diuretics can be recommended. Because of concerns about the lower effectiveness of calcium channel blockers in decreasing coronary events and heart failure and in reducing progression of renal disease in diabetes, it is recommended to use these agents as second-line drugs for patients who cannot tolerate the other preferred classes or who require additional agents to achieve the target blood pressure. The choice depends on the patients specific treatment indications since each of these drugs have potential advantages and disadvantages. In patients with microalbuminuria or clinical nephropathy, both ACE-inhibitors and angiotensin receptor blockers are considered first line therapy for the prevention of and progression of nephropathy. Since treatment is usually life-long, cost effectiveness should be included in treatment evaluation.

Risk of adverse effects of intensified treatment in insulin-dependent diabetes mellitus: a meta-analysis

While the benefits of intensified insulin treatment in insulin-dependent (Type 1) diabetes mellitus (IDDM) are well recognized, the risks have not been comprehensively characterized. We examined the risk of severe hypoglycaemia, ketoacidosis, and death in a meta-analysis of randomized controlled trials. The MEDLINE database, reference lists, and specialist journals were searched electronically or by hand to identify relevant studies with at least 6 months of follow-up and the monitoring of glycaemia by glycosylated haemoglobin measurements. Logistic regression was used for calculation of combined odds ratios and 95% confidence intervals (95% CI). The influence of covariates was examined by including covariate-by-treatment interaction terms. Methodological study quality was assessed and sensitivity analyses were performed. Fourteen trials were identified. These contributed 16 comparisons with 1028 patients allocated to intensified and 1039 allocated to conventional treatment. A total of 846 patients suffered at least one episode of severe hypoglycaemia, 175 patients experienced ketoacidosis and 26 patients died. The combined odds ratio (95% CI) for hypoglycaemia was 2.99 (2.45-3.64), for ketoacidosis 1.74 (1.27-2.38) and for death from all causes 1.40 (0.65-3.01). The risk of severe hypoglycaemia was determined by the degree of normalization of glycaemia achieved (p=0.005 for interaction term), with the results from the Diabetes Control and Complications Trial (DCCT) in line with the other trials. Ketoacidosis risk depended on the type of intensified treatment used. Odds ratios (95% CI) were 7.20 (2.95-17.58) for exclusive use of pumps, 1.13 (0.15-8.35) for multiple daily injections and 1.28 (0.90-1.83) for trials offering a choice between the two (p = 0.004 for interaction). Mortality was significantly (p = 0.007) increased for causes potentially associated with acute complications (7 vs 0 deaths, 5 deaths attributed to ketoacidosis, and 2 sudden deaths), and non-significantly (p = 0.16) decreased for macrovascular causes (3 vs 8 deaths). We conclude that there is a substantial risk of severe adverse effects associated with intensified insulin treatment. Mortality from acute metabolic causes is increased; however, this is largely counterbalanced by a reduction in cardiovascular mortality. The excess of severe hypoglycemia in the DCCT is not exceptional. Multiple daily injection schemes may be safer than treatment with insulin pumps.

[Will type I diabetes mellitus be treated with immunosuppressive drugs in the future?]

Even if the pathogenesis of type-I (insulin-dependent) diabetes mellitus is still not clarified in every detail, there is general agreement that this form of diabetes is induced by autoimmune mechanisms leading to beta-cell destruction. Therefore, it should theoretically be feasible to suppress the mechanism leading to type-I diabetes with appropriate and early immunotherapy. The current clinical data clearly document that the rate and duration of remissions in patients with newly diagnosed type-I diabetes can be increased significantly using appropriate immunosuppressive regimens. However, before these therapies can become standard therapy of type-I diabetes, the following important clinical requirements have to be fulfilled: the toxicity (especially to kidneys and beta-cells) has to be reduced, the patients should be diagnosed and treated in 'pre-diabetic' states, more selective immunosuppressive regimens have to be available in order to reduce the occurrence of treatment-associated lymphomas and neoplasias. Since accurate detection of 'pre-diabetic' patients is difficult and presents an immense logistic problem, it may take a long time before large-scale immunosuppressive therapies of type-I diabetes are feasible.

Establishing glycaemic control with continuous subcutaneous insulin infusion in children and adolescents with type 1 diabetes: experience of the PedPump Study in 17 countries

AIMS/HYPOTHESIS: To assess the use of paediatric continuous subcutaneous infusion (CSII) under real-life conditions by analysing data recorded for up to 90 days and relating them to outcome. METHODS: Pump programming data from patients aged 0-18 years treated with CSII in 30 centres from 16 European countries and Israel were recorded during routine clinical visits. HbA(1c) was measured centrally. RESULTS: A total of 1,041 patients (age: 11.8 +/- 4.2 years; diabetes duration: 6.0 +/- 3.6 years; average CSII duration: 2.0 +/- 1.3 years; HbA(1c): 8.0 +/- 1.3% [means +/- SD]) participated. Glycaemic control was better in preschool (n = 142; 7.5 +/- 0.9%) and pre-adolescent (6-11 years, n = 321; 7.7 +/- 1.0%) children than in adolescent patients (12-18 years, n = 578; 8.3 +/- 1.4%). There was a significant negative correlation between HbA(1c) and daily bolus number, but not between HbA(1c) and total daily insulin dose. The use of <6.7 daily boluses was a significant predictor of an HbA(1c) level >7.5%. The incidence of severe hypoglycaemia and ketoacidosis was 6.63 and 6.26 events per 100 patient-years, respectively. CONCLUSIONS/INTERPRETATION: This large paediatric survey of CSII shows that glycaemic targets can be frequently achieved, particularly in young children, and the incidence of acute complications is low. Adequate substitution of basal and prandial insulin is associated with a better HbA(1c).

[Insulin and type 2 diabetes mellitus]

Worldwide an increasing number of persons suffers from type 2 diabetes. Often treatment with oral hypoglycemic agents is not sufficient for adequate glycemic control and additional insulin treatment is necessary. Treatment with insulin is recommended if HbA1c levels below 7% cannot be achieved despite lifestyle measures and the proper use of oral hypoglycemic agents. In addition, pregnancy, periods pre and post major operations, treatment in intensive care units, glucocorticoid medication, severe peripheral neuropathy as well as contraindications of oral hypoglycaemic agents may be indications for insulin therapy irrespective of the actual glycemic control. The choice of the appropriate insulin regimen depends on the daily blood glucose profiles and patient needs.

A reduction in severe hypoglycaemia in type 1 diabetes in a randomized crossover study of continuous intraperitoneal compared with subcutaneous insulin infusion

Continuous intraperitoneal insulin infusion (CIPII) with the DiaPort system using regular insulin was compared to continuous subcutaneous insulin infusion (CSII) using insulin Lispro, to investigate the frequency of hypoglycemia, blood glucose control, quality of life, and safety.

IGF-I treatment in adults with type 1 diabetes: effects on glucose and protein metabolism in the fasting state and during a hyperinsulinemic-euglycemic amino acid clamp

Type 1 diabetes is associated with abnormalities of the growth hormone (GH)-IGF-I axis. Such abnormalities include decreased circulating levels of IGF-I. We studied the effects of IGF-I therapy (40 microg x kg(-1) x day(-1)) on protein and glucose metabolism in adults with type 1 diabetes in a randomized placebo-controlled trial. A total of 12 subjects participated, and each subject was studied at baseline and after 7 days of treatment, both in the fasting state and during a hyperinsulinemic-euglycemic amino acid clamp. Protein and glucose metabolism were assessed using infusions of [1-13C]leucine and [6-6-2H2]glucose. IGF-I administration resulted in a 51% rise in circulating IGF-I levels (P < 0.005) and a 56% decrease in the mean overnight GH concentration (P < 0.05). After IGF-I treatment, a decrease in the overnight insulin requirement (0.26+/-0.07 vs. 0.17+/-0.06 U/kg, P < 0.05) and an increase in the glucose infusion requirement were observed during the hyperinsulinemic clamp (approximately 67%, P < 0.05). Basal glucose kinetics were unchanged, but an increase in insulin-stimulated peripheral glucose disposal was observed after IGF-I therapy (37+/-6 vs. 52+/-10 micromol x kg(-1) x min(-1), P < 0.05). IGF-I administration increased the basal metabolic clearance rate for leucine (approximately 28%, P < 0.05) and resulted in a net increase in leucine balance, both in the basal state and during the hyperinsulinemic amino acid clamp (-0.17+/-0.03 vs. -0.10+/-0.02, P < 0.01, and 0.25+/-0.08 vs. 0.40+/-0.06, P < 0.05, respectively). No changes in these variables were recorded in the subjects after administration of placebo. These findings demonstrated that IGF-I replacement resulted in significant alterations in glucose and protein metabolism in the basal and insulin-stimulated states. These effects were associated with increased insulin sensitivity, and they underline the major role of IGF-I in protein and glucose metabolism in type 1 diabetes.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

A real time simulation model of glucose-insulin metabolism for type 1 diabetes patients

In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.

A neural network approach for insulin regime and dose adjustment in type 1 diabetes

A decision support system based on a neural network approach is proposed to advise on insulin regime and dose adjustment for type 1 diabetes patients.