Digital health tools to promote diabetes education and management of cardiovascular risk factors among under-resourced populations

Diabetes is a major risk factor for the development of cardiovascular disease, the leading cause of death in the United States, further highlighting the need for improved diabetes management, particularly among individuals from ethnic minorities or low socioeconomic status

Predictors of Dropouts From a San Diego Diabetes Program: A Case Control Study

INTRODUCTION: The objective of this study was to determine the demographic, treatment, clinical, and behavioral factors associated with dropping out of a nurse-based, low-income, multiethnic San Diego diabetes program. METHODS: Data were collected during a 17-month period in 2000 and 2002 on patients with type 2 diabetes from Project Dulce, a disease management program in San Diego County designed to care for an underserved diabetic population. The study sample included 69 cases and 504 controls representing a racial/ethnic mix of 53% Hispanic, 7% black, 16% Asian, 22% white, and 2% other. Logistic regression was used to determine factors associated with patient dropout. RESULTS: Patients who had high initial clinical indicators including blood pressure and hemoglobin A1c and those who smoked currently or smoked in the past were more likely to drop out of the diabetes program. CONCLUSION: This study provides markers of patient dropout in a low-income, multiethnic, type 2 diabetic population. Reasons for dropout in this program can be investigated to prevent further cohort loss

Imaging of Oxidation-Specific Epitopes in Atherosclerosis and Macrophage-Rich Vulnerable Plaques

Oxidative stress, and in particular oxidation of lipoproteins, is a hallmark of atherosclerosis. Upon entry of lipoproteins into the vessel wall, a cascade of pro-atherogenic pathways is initiated whereby the reaction of reactive oxygen species with substrates amenable to oxidation, such as polyunsaturated fatty acids, generates a variety of oxidation-specific epitopes on lipoproteins, proteins in the vessel wall, and apoptotic macrophages. Several of these oxidation-specific epitopes have been well characterized and specific murine and fully human antibodies have been generated in our laboratory to detect them in the vessel wall. We have developed radionuclide, gadolinium and iron oxide based MRI techniques to noninvasively image oxidation-specific epitopes in atherosclerotic lesions. These approaches quantitate plaque burden and also allow detection of atherosclerosis regression and plaque stabilization. In particular, gadolinium micelles or lipid-coated ultrasmall superparamagnetic iron oxide particles containing oxidation-specific antibodies accumulate within macrophages in the artery wall, suggesting they may image the most unstable plaques. Translation of these approaches to humans may allow a sensitive technique to image and monitor high-risk atherosclerotic lesions and may guide optimal therapeutic interventions

The relationship between HbA1c and hypoglycaemia in patients with diabetes treated with insulin degludec versus insulin glargine 100 units/mL

Aim Treat‐to‐target, randomized controlled trials have confirmed lower rates of hypoglycaemia at equivalent glycaemic control with insulin degludec (degludec) versus insulin glargine 100 units/mL (glargine U100) in patients with type 1 (T1D) or type 2 diabetes (T2D). Treat‐to‐target trials are designed to enable comparisons of safety and tolerability at a similar HbA1c level. In this post hoc analysis of the SWITCH 1 and 2 trials, we utilised a patient‐level modelling approach to compare how glycaemic control might differ between basal insulins at a similar rate of hypoglycaemia. Materials and Methods Data for HbA1c and symptomatic hypoglycaemia from the SWITCH 1 and SWITCH 2 trials were analyzed separately for patients with type 1 diabetes and type 2 diabetes, respectively. The association between the individual patient‐level risk of hypoglycaemia and HbA1c was investigated using a Poisson regression model and used to estimate potential differences in glycaemic control with degludec versus glargine U100, at the same rate of hypoglycaemia. Results Improvements in glycaemic control increased the incidence of hypoglycaemia with both basal insulins across diabetes types. Our analysis suggests that patients could achieve a mean HbA1c reduction of 0.70 [0.05; 2.20]95% CI (for type 1 diabetes) or 0.96 [0.39; 1.99]95% CI (for type 2 diabetes) percentage points (8 [1; 24]95% CI or 10 [4; 22]95% CI mmol/mol, respectively) further with degludec than with glargine U100 before incurring an equivalent risk of hypoglycaemia. Conclusion Our findings suggest that patients in clinical practice may be able to achieve lower glycaemia targets with degludec versus glargine U100, before incurring an equivalent risk of hypoglycaemia

Empirical Likelihood Inference for the Area Under the ROC Curve

For a continuous-scale diagnostic test, the most commonly used summary index of the receiver operating characteristic (ROC) curve is the area under the curve (AUC) that measures the accuracy of the diagnostic test. In this paper we propose an empirical likelihood approach for the inference of AUC. We first define an empirical likelihood ratio for AUC and show that its limiting distribution is a scaled chi-square distribution. We then obtain an empirical likelihood based confidence interval for AUC using the scaled chi-square distribution. This empirical likelihood inference for AUC can be extended to stratified samples and the resulting limiting distribution is a weighted sum of independent chi-square distributions. We also conduct simulation studies to compare the relative performance of the proposed empirical likelihood based interval with the existing normal approximation based intervals and bootstrap intervals for AUC