Clinical significance of cardiovascular dysmetabolic syndrome

Although diabetes mellitus is predominantly a metabolic disorder, recent data suggest that it is as much a vascular disorder. Cardiovascular complications are the leading cause of death and disability in patients with diabetes mellitus. A number of recent reports have emphasized that many patients already have atherosclerosis in progression by the time they are diagnosed with clinical evidence of diabetes mellitus. The increased risk of atherosclerosis and cardiovascular complications in diabetic patients is related to the frequently associated dyslipidemia, hypertension, hyperglycemia, hyperinsulinemia, and endothelial dysfunction. The evolving knowledge regarding the variety of metabolic, hormonal, and hemodynamic abnormalities in patients with diabetes mellitus has led to efforts designed for early identification of individuals at risk of subsequent disease. It has been suggested that insulin resistance, the key abnormality in type II diabetes, often precedes clinical features of diabetes by 5–6 years. Careful attention to the criteria described for the cardiovascular dysmetabolic syndrome should help identify those at risk at an early stage. The application of nonpharmacologic as well as newer emerging pharmacologic therapies can have beneficial effects in individuals with cardiovascular dysmetabolic syndrome and/or diabetes mellitus by improving insulin sensitivity and related abnormalities. Early identification and implementation of appropriate therapeutic strategies would be necessary to contain the emerging new epidemic of cardiovascular disease related to diabetes

A mathematical model for the burden of diabetes and its complications

BACKGROUND: The incidence and prevalence of diabetes are increasing all over the world. Complications of diabetes constitute a burden for the individuals and the whole society. METHODS: In the present paper, ordinary differential equations and numerical approximations are used to monitor the size of populations of diabetes with and without complications. RESULTS: Different scenarios are discussed according to a set of parameters and the dynamical evolution of the population from the stage of diabetes to the stage of diabetes with complications is clearly illustrated. CONCLUSIONS: The model shows how efficient and cost-effective strategies can be obtained by acting on diabetes incidence and/or controlling the evolution to the stage of complications

Prognostic value of CT coronary angiography in diabetic and non-diabetic subjects with suspected CAD: importance of presenting symptoms

AIM: To assess the prognostic relevance of 64-slice computed tomography coronary angiography (CT-CA) and symptoms in diabetics and non-diabetics referred for cardiac evaluation. METHODS: We followed 210 patients with diabetes type 2 (DM) and 203 non-diabetic patients referred for CT-CA for ruling out coronary artery disease (CAD). Patients were without known history of CAD and were divided into four categories on the basis of symptoms at presentation (none, atypical angina, typical angina and dyspnoea). Clinical end points were major cardiac events (MACE): cardiac-related death, non-fatal myocardial infarction, unstable angina and cardiac revascularizations. Cox proportional hazard models, with and without adjustment for risk factors and multiplicative interaction term (obstructive CAD 7 DM), were developed to predict outcome. RESULTS: DM patients with dyspnoea or who were asymptomatic showed a higher prevalence of obstructive CAD than non-diabetics (p\u2009 64\u20090.01). At mean follow-up of 20.4 months, DM patients had worse cardiac event-free survival in comparison with non-DM patients (90% vs. 81%, p\u2009=\u20090.02). In multivariate analysis, CT-CA evidence of obstructive CAD (in DM patients: HR: 6.4; 95% CI: 2.3-17.5; p\u2009100 in non-DM patients (HR: 5.6; 95% CI: 1.4-21.5; p\u2009=\u20090.01). In Cox regression analysis of the overall population, interaction term obstructive CAD 7 DM resulted in non-significance. CONCLUSIONS: Among DM patients, dyspnoea carried a high event risk with a MACE rate four times higher. CT-CA findings were strongly predictive of outcome and proved valuable for further risk stratification

Association of an APOC3 promoter variant with type 2 diabetes risk and need for insulin treatment in lean persons

Aims/hypothesis: An APOC3 promoter haplotype has been previously associated with type 1 diabetes. In this population-based study, we investigated whether APOC3 polymorphisms increase type 2 diabetes risk and need for insulin treatment in lean participants. Methods: In the Rotterdam Study, a population-based prospective cohort (n = 7,983), Cox and logistic regression models were used to analyse the associations and interactive effects of APOC3 promoter variants (-482C > T, -455T > C) and BMI on type 2 diabetes risk and insulin treatment. Analyses were followed by replication in an independent case-control sample (1,817 cases, 2,292 controls) and meta-analysis. Results: In lean participants, the -482T allele was associated with increased risk of prevalent and incident type 2 diabetes: OR -482CT 1.47 (95% CI 1.13-1.92), -482TT 1.40 (95% CI 0.83-2.35), p = 0.009 for trend; HR -482CT 1.35 (95% CI 0.96-1.89), -482TT 1.68 (95% CI 0.91-3.1), p = 0.03 for trend, respectively. These results were confirmed by replication. Meta-analysis was highly significant (-482T meta-analysis p = 1.1 × 10-4). A borderline significant interaction was observed for insulin use among participants with type 2 diabetes (-482CT*BMI p = 0.06, -455TC*BMI p = 0.02). Conclusions/interpretation: At a population-based level, the influence of APOC3 promoter variants on type 2 diabetes risk varies with the level of adiposity. Lean carriers of the -482T allele had increased type 2 diabetes risk, while such an effect was not observed in overweight participants. Conversely, in overweight participants the -455C allele seemed protective against type 2 diabetes. The interaction of the variants with need for insulin treatment may indicate beta cell involvement in lean participants. Our findings suggest overlap in the genetic backgrounds of type 1 diabetes and type 2 diabetes in lean patients

The pediatric NAFLD fibrosis index: a predictor of liver fibrosis in children with non-alcoholic fatty liver disease

<p>Abstract</p> <p>Background</p> <p>Liver fibrosis is a stage of non-alcoholic fatty liver disease (NAFLD) which is responsible for liver-related morbidity and mortality in adults. Accordingly, the search for non-invasive markers of liver fibrosis has been the subject of intensive efforts in adults with NAFLD. Here, we developed a simple algorithm for the prediction of liver fibrosis in children with NAFLD followed at a tertiary care center.</p> <p>Methods</p> <p>The study included 136 male and 67 female children with NAFLD aged 3.3 to 18.0 years; 141 (69%) of them had fibrosis at liver biopsy. On the basis of biological plausibility, readily availability and evidence from adult studies, we evaluated the following potential predictors of liver fibrosis at bootstrapped stepwise logistic regression: gender, age, body mass index, waist circumference, alanine transaminase, aspartate transaminase, gamma-glutamyl-transferase, albumin, prothrombin time, glucose, insulin, triglycerides and cholesterol. A final model was developed using bootstrapped logistic regression with bias-correction. We used this model to develop the 'pediatric NAFLD fibrosis index' (PNFI), which varies between 0 and 10.</p> <p>Results</p> <p>The final model was based on age, waist circumference and triglycerides and had a area under the receiver operating characteristic curve of 0.85 (95% bootstrapped confidence interval (CI) with bias correction 0.80 to 0.90) for the prediction of liver fibrosis. A PNFI ≥ 9 (positive likelihood ratio = 28.6, 95% CI 4.0 to 201.0; positive predictive value = 98.5, 95% CI 91.8 to 100.0) could be used to rule in liver fibrosis without performing liver biopsy.</p> <p>Conclusion</p> <p>PNFI may help clinicians to predict liver fibrosis in children with NAFLD, but external validation is needed before it can be employed for this purpose.</p

A critical review of mathematical models and data used in diabetology

The literature dealing with mathematical modelling for diabetes is abundant. During the last decades, a variety of models have been devoted to different aspects of diabetes, including glucose and insulin dynamics, management and complications prevention, cost and cost-effectiveness of strategies and epidemiology of diabetes in general. Several reviews are published regularly on mathematical models used for specific aspects of diabetes. In the present paper we propose a global overview of mathematical models dealing with many aspects of diabetes and using various tools. The review includes, side by side, models which are simple and/or comprehensive; deterministic and/or stochastic; continuous and/or discrete; using ordinary differential equations, partial differential equations, optimal control theory, integral equations, matrix analysis and computer algorithms

The Use of Biomaterials in Islet Transplantation

Pancreatic islet transplantation is a therapeutic option to replace destroyed β cells in autoimmune diabetes. Islets are transplanted into the liver via the portal vein; however, inflammation, the required immunosuppression, and lack of vasculature decrease early islet viability and function. Therefore, the use of accessory therapy and biomaterials to protect islets and improve islet function has definite therapeutic potential. Here we review the application of niche accessory cells and factors, as well as the use of biomaterials as carriers or capsules, for pancreatic islet transplantation

Hemoglobin A1c measurement for the diagnosis of Type 2 diabetes in children

<p>Abstract</p> <p>Laboratory measurements of hemoglobin A1c above 6.5% were approved as an additional diagnostic criteria for diabetes mellitus by the American Diabetes Association in 2010. Several recent pediatric studies have cast HbA1c measurement in children in an unfavorable light in the pediatric population, by comparing HbA1c measurements to results on oral glucose tolerance test (OGTT) or fasting plasma glucose (FPG). However, many of these studies do not recognize that diabetes diagnostic criteria are based upon long-term health outcomes. In this sense, OGTT and FPG have themselves never been validated in the pediatric population. Studies to validate diagnostic tests for diabetes in pediatric populations may take a substantial period of time, and may prove unfeasible. However, studies that tie diagnostic results as a child to diagnostic results as an adult may be more feasible and may provide the data needed to determine which pediatric diagnostic criteria to use. Thus, for the time being, except for cases of hemoglobinopathy, cystic fibrosis, and a few other exceptions, describing HbA1c as ‘lacking in sensitivity or specificity’ in the pediatric population because of lack of correlation with OGTT is not scientifically sound.</p