The Value of Information Technology-Enabled Diabetes Management

Reviews different technologies used in diabetes disease management, as well as the costs, benefits, and quality implications of technology-enabled diabetes management programs in the United States

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

Investigating the Molecular Mechanism of Aqueous Extract of Cyclocarya paliurus on Ameliorating Diabetes by Transcriptome Profiling

Diabetes is generally regarded as a metabolic disorder disease caused by various reasons, including pancreas islet injury and lipid metabolism disorders. The aqueous extract of Cyclocarya paliurus leaves (CPAE) was reported to be anti-diabetic. However, the possible molecular mechanisms have not been investigated. To elucidate the anti-diabetic effects of CPAE and the underlying potential mechanisms, we performed transcriptome profiling (RNA-Seq and miRNA-Seq) on the pancreas and liver from non-diabetic, diabetic and diabetic-CPAE rats. Our results demonstrated the CPAE could reduce excessive oxidative stress and inflammation in the pancreas, and maintain the balance of glucose and lipid metabolism in the liver. Transcriptome profiling and regulatory network analysis indicated that CPAE may ameliorate diabetes through improving β-cell survival and strengthening insulin secretion in the pancreas. Meanwhile, CPAE could improve impaired lipid metabolism and reduce excessive oxidative damage in the liver probably through miR-200/375-Aldh1b1/Hps5-Hes1 co-regulatory network. Taken together, our biochemical experiments combined with transcriptome profiling showed that the effects of CPAE on anti-diabetes may work through protecting pancreatic β-cell, improving dyslipidaemia and lipid metabolism disorders

Equal Care, Unequal Outcomes: Experiences of a REACH 2010 Community

Diabetes is growing in prevalence and costs. Guidelines for care have been available since 1983, yet diabetes care and outcomes remain less than ideal. CDC’s Racial and Ethnic Approaches to Community Health 2010 (REACH 2010) identified diabetes in African Americans as a priority for action. This article documents the activities, interventions, and current progress of the REACH 2010 diabetes coalition formed in Charleston and Georgetown counties, South Carolina, in reducing health care disparities and describes next steps for improving outcomes. The Chronic Care Model guided many of the implementation activities, and chart audits were used to document outcomes. Ambulatory care visits (N = 1522) between 2000 and 2004 were reviewed. Significant progress has been made in reducing disparities in process measures, but similar reductions for intermediate outcomes have not been observed

Dynamic Decision Models for Managing the Major Complications of Diabetes

Diabetes is the sixth-leading cause of death and a major cause of cardiovascular and renal diseases in the U.S. In this dissertation, we consider the major complications of diabetes and develop dynamic decision models for two important timing problems: Transplantation in prearranged paired kidney exchanges (PKEs) and statin initiation. Transplantation is the most viable renal replacement therapy for end-stage renal disease (ESRD) patients, but there is a severe disparity between the demand and supply of kidneys for transplantation. PKE, a cross-exchange of kidneys between incompatible patient-donor pairs, overcomes many difficulties in matching patients with incompatible donors. In a typical PKE, transplantation surgeries take place simultaneously so that no donor may renege after her intended recipient receives the kidney. We consider two autonomous patients with probabilistically evolving health statuses in a PKE, and model their transplant timing decisions as a discrete-time non-zero-sum stochastic game. We explore necessary and sufficient conditions for patients' decisions to form a stationary-perfect equilibrium, and formulate a mixed-integer linear programming (MIP) representation of equilibrium constraints to characterize a socially optimal stationary-perfect equilibrium. We calibrate our model using large scale clinical data. We quantify the social welfare loss due to patient autonomy and demonstrate that the objective of maximizing the number of transplants may be undesirable. Patients with Type 2 diabetes have higher risk of heart attack and stroke, and if not treated these risks are confounded by lipid abnormalities. Statins can be used to treat such abnormalities, but their use may lead to adverse outcomes. We consider the question of when to initiate statin therapy for patients with Type 2 diabetes. We formulate a Markov decision process (MDP) to maximize the patient's quality-adjusted life years (QALYs) prior to the first heart attack or stroke. We derive sufficient conditions for the optimality of control-limit policies with respect to patient's lipid-ratio (LR) levels and age and parameterize our model using clinical data. We compute the optimal treatment policies and illustrate the importance of individualized treatment factors by comparing their performance to those of the guidelines in use in the U.S

Predictors of glycemic control among patients with Type 2 diabetes: A longitudinal study

BACKGROUND: Diabetes is the sixth leading cause of death and results in significant morbidity. The purpose of this study is to determine what demographic, health status, treatment, access/quality of care, and behavioral factors are associated with poor glycemic control in a Type 2 diabetic, low-income, minority, San Diego population. METHODS: Longitudinal observational data was collected on patients with Type 2 diabetes from Project Dulce, a program in San Diego County designed to care for an underserved diabetic population. The study sample included 573 patients with a racial/ethnic mix of 53% Hispanic, 7% black, 18% Asian, 20% white, and 2% other. We utilized mixed effects models to determine the factors associated with poor glycemic control using hemoglobin A1C (A1C) as the outcome of interest. A multi-step model building process was used resulting in a final parsimonious model with main effects and interaction terms. RESULTS: Patients had a mean age of 55 years, 69% were female, the mean duration of diabetes was 7.1 years, 31% were treated with insulin, and 57% were obese. American Diabetes Association (ADA) recommendations for blood pressure and total cholesterol were met by 71% and 68%, respectively. Results of the mixed effects model showed that patients who were uninsured, had diabetes for a longer period of time, used insulin or multiple oral agents, or had high cholesterol had higher A1C values over time indicating poorer glycemic control. The younger subjects also had poorer control. CONCLUSION: This study provides factors that predict glycemic control in a specific low-income, multiethnic, Type 2 diabetic population. With this information, subgroups with high risk of disease morbidity were identified. Barriers that prevent these patients from meeting their goals must be explored to improve health outcomes

Type 2 diabetes in South Asians compared to Europeans: higher risk and earlier development of major cardiovascular events irrespective of the presence and degree of retinopathy. Results from The HinDu The Hague Diabetes Study

Introduction South Asians with diabetes have more severe diabetic retinopathy (DR) and cardiovascular complications than white Caucasians. However, how big this gap is and the relation with the severity of DR has not been studied. Here, we quantify the difference in time from diabetes diagnosis until a first non-fatal Major Adverse Cardiovascular Event (TUF MACE) in different DR groups in South Asians and Europeans. Methods 3831 adults with type 2 diabetes, 1358 South Asians and 2473 Europeans, treated in our diabetes clinic between 2006 and 2017 were included. Data on risk factors, diabetes duration, age of diagnosis and diabetes complications were collected from the diabetes-specific database and analysed using descriptive statistics and Cox regression. DR was graded in 3 categories, and non-fatal MACE was pre-specified. Results Prevalence of non-fatal MACE was the same when DR was absent, increased with increasing severity of DR in both ethnic groups, but was more frequent in South Asians with DR (mild: 50 vs. 42% and severe 62 vs. 46%. Classic risk factors only differed in relation to smoking habits, which were significantly lower in South Asians. After correction for classic risk factors and age at diabetes diagnosis TUF MACE was significantly shorter in South Asians, an effect also seen in the no-DR group (4.1 yrs. HR 1.5, 95% CI 1.3-1.8 and 7.4 yrs. earlier, HR 2.0, 95% CI 1.6-2.6 for no-DR and severe DR, respectively). Conclusions When adjusted for age at diabetes diagnosis, we show that time until first non-fatal MACE in South Asians is significantly shorter compared to Europeans and increases from no- to severe DR.Prevention, Population and Disease management (PrePoD)Public Health and primary car

Quorum sensing and Biofilm formation by Bacterial Isolates from Hemodialysis Patients

In this study, blood and urine samples were collected from (60) patients with hemodialysis with age range between (12-82) years old from both sexes. All samples were subjected to identify the bacterial aerobic cultivation. Different types of bacteria were isolated that caused septicemia or urinary tract infection. The predominant bacteria were E. coli for Gram negative, and S. aureus for gram positive. Quorum sensing were studied for E. coli and K. pneumoniae and the results shown that all tested bacteria show an aggregation of the bacterial cells in the presence of homoserine lactone and the best interval for accumulation of homoserine lactone was after 4 hours in E. coli, 2 hours in K. pneumoniae. biofilm formation were studied for all bacterial isolates and the results shown that the all bacteria can form biofilm, S. epidermidis (87.5%), S. aureus (85.7%) as strong where E. coli and Proteus mirabilis show moderate biofilm formation

Role of Micrornas in Intestinal Inflammation and Barrier Homeostasis after Alcohol and Burn Injury

MicroRNAs are small noncoding RNA molecules that negatively regulate gene expression. Within the intestinal epithelium, miRNAs play a critical role in gut homeostasis and aberrant miRNA expression has been implicated in various disorders associated with intestinal inflammation and barrier disruption. In this study, we sought to profile changes in intestinal epithelial cell miRNA expression after alcohol and burn injury and elucidate their impact on inflammation and barrier integrity. In a more targeted approach, we began by focusing on anti-inflammatory miRNAs that, when downregulated, could exacerbate inflammation and result in intestinal barrier disruption. Using a mouse model of acute ethanol intoxication and burn injury, we found that small intestinal epithelial cell expression of miR-146a is significantly decreased one day following injury. Using in vitro studies, we demonstrate that miR-146a inhibition in small intestinal epithelial cells promotes, while miR-146a overexpression prevents, LPS induced inflammation. Further mechanistic studies revealed that reduced miR-146a promotes intestinal epithelial cell inflammation by promoting p38 MAPK signaling via increased levels of its target TRAF6. Furthermore, we demonstrate that in vivo miR-146a overexpression significantly inhibits intestinal inflammation one day following combined injury and potentially supports intestinal barrier homeostasis. In a secondary approach, we integrated miRNA and mRNA sequencing with miRNA target gene databases as a non-biased approach to generate a network of dysregulated miRNAs of interest after alcohol and burn injury. Our results identify several miRNAs which could promote gut barrier disruption after alcohol and burn injury, including upregulation of miR-98-3p and miR-381-3p, which is associated with reduced proliferation, upregulation of miR-29a-3p, miR-429-3p and miR3535, which can reduce cellular adhesion, and downregulation of Let-7d-5p and miR-130b-5p, which is linked to apoptosis. Overall, this study highlights the important impact that miRNA expression can have the intestinal homeostasis and the valuable potential of harnessing aberrant miRNA expression as a therapeutic target to control intestinal inflammation

Conference Program [2014]

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