Type 1 diabetes

Type 1 diabetes is a chronic autoimmune disease characterised by insulin deficiency and resultant hyperglycaemia. Knowledge of type 1 diabetes has rapidly increased over the past 25 years, resulting in a broad understanding about many aspects of the disease, including its genetics, epidemiology, immune and β-cell phenotypes, and disease burden. Interventions to preserve β cells have been tested, and several methods to improve clinical disease management have been assessed. However, wide gaps still exist in our understanding of type 1 diabetes and our ability to standardise clinical care and decrease disease-associated complications and burden. This Seminar gives an overview of the current understanding of the disease and potential future directions for research and care

Established and emerging biomarkers for the prediction of type 1 diabetes: a systematic review

Type 1 diabetes (T1D) is an autoimmune disease with a prolonged and variable latent period that culminates in the destruction of pancreatic β-cells and the development of hyperglycemia. There is a need for diagnostic biomarkers to detect more accurately detect individuals with prediabetes to expedite targeting for prevention and intervention strategies. To assess the current ability to predict the insidious development of T1D, we conducted a comprehensive systematic review for established and prospective predictive markers of T1D using the Medline, OVID, and EMBASE databases. Resulting citations were screened for relevance to subject. Our research generated five major categories of markers that are either currently used or forthcoming: genetic, autoantibodies, risk score quantification, cellular immunity, and β-cell function. The current standard used to assess T1D onset or predisposition focuses on autoimmune pathology and disease-associated autoantibodies. Research studies in general go beyond autoantibody screening and assess genetic predisposition, and quantitate risk of developing disease based on additional factors. However, there are few currently used techniques that assess the root of T1D: β-cell destruction. Thus, novel techniques are discussed with the potential to gauge degrees of β-cell stress and failure via protein, RNA, and DNA analyses

Comprehensive User Engagement Sites (CUES) in Philadelphia: A Constructive Proposal

This paper is a study about Philadelphia’s comprehensive user engagement sites (CUESs) as the authors address and examine issues related to the upcoming implementation of a CUES while seeking solutions for its disputed questions and plans. Beginning with the federal drug schedules, the authors visit some of the medical and public health issues vis-à-vis safe injection facilities (SIFs). Insite, a successful Canadian SIF, has been thoroughly researched as it represents a paradigm for which a Philadelphia CUES can expand upon. Also, the existing criticisms against SIFs are revisited while critically unpackaged and responded to in favor of the establishment. In the main section, the authors propose the layout and services of the upcoming CUES, much of which would be in congruent to Vancouver’s Insite. On the other hand, the CUES would be distinct from Insite, as the authors emphasize, in that it will offer an information center run by individuals in recovery and place additional emphasis on early education for young healthcare professionals by providing them a platform to work at the site. The paper will also briefly investigate the implementation of a CUES site under an ethical scope of the Harm Reduction Theory. Lastly, the authors recommend some strategic plans that the Philadelphia City government may consider employing at this crucial stage

Bone Density in Children with Single Ventricle Physiology

Background Children with chronic diseases are at risk for low bone mineral density (BMD). There are no studies of BMD in children with congenital heart disease and particularly SV. Children with this defect are often treated with warfarin, suspected to negatively impact BMD in adults. We assessed BMD in patients with single ventricle (SV) physiology and compared the BMD of subjects taking warfarin to those who were not. Methods Subjects 5-12 years with SV were included. BMD z-scores by dual-energy X-ray absorptiometry (DXA) of the spine and total body less head (TBLH) were obtained. Calcium intake, activity level, height, and Tanner stage were assessed. Linear regression models and t-tests were used to investigate differences between participants and normative data as well as between subjects' subgroups. Results Twenty six subjects were included; 16 took warfarin. Mean BMD z-score at the spine was significantly lower than expected at -1.0±0.2 (p<0.0001), as was the BMD z-score for TBLH at - 0.8±0.2 (p<0.0001). Those results remained significant after adjusting for height. Subjects who were on warfarin tended to have lower BMD at both the spine and TBLH than those who were not, with a z-score difference of 0.6±0.46 at the spine (p=0.106) and a difference of 0.4±0.34 at TBLH (p=0.132). Conclusions BMD is significantly reduced in children with SV. Warfarin appears to lower BMD but the effect is less conclusive. Continued evaluation is recommended for these patients at risk for reduced bone density. Evaluation of other cardiac patients on warfarin therapy should also be considered

Using a cell phone-based glucose monitoring system for adolescent diabetes management

INTRODUCTION: Mobile technology may be useful in addressing several issues in adolescent diabetes management. PURPOSE: To assess the feasibility and acceptability of a cell phone glucose monitoring system for adolescents with type 1 diabetes and their parents. METHODS: The authors recruited patients with type 1 diabetes who had been diagnosed for at least 1 year. Each adolescent used the system for 6 months, filling out surveys every 3 months to measure their usability and satisfaction with the cell phone glucose monitoring system, as well as how use of the system might affect quality of family functioning and diabetes management. RESULTS: Adolescents reported positive feelings about the technology and the service, even though a concerning number of them had significant technical issues that affected continued use of the device. Nearly all thought that the clinic involvement in monitoring testing behavior was quite acceptable. The use of the Glucophone™ did not, however, significantly change the quality of life of the adolescents, their level of conflict with their parents, their reported self-management of diabetes, or their average glycemic control within the short time frame of the study. CONCLUSIONS: As a feasibility study of the technology, this work was successful in demonstrating that cell phone glucose monitoring technology can be used in an adolescent population to track and assist in self-monitoring behavior. The authors speculate that explicitly attempting to change behavior, perhaps with the use of behavioral contracts, would enhance the technology's ability to improve outcomes

The Relationship of Worry About Hypoglycemia With Diabetes-specific and Typical Youth Behavior Among Emerging Adults With Type 1 Diabetes

PURPOSE: Little is known about the relationship of worry about hypoglycemia with diabetes-specific and typical youth behaviors among emerging adults with type 1 diabetes. This study's purpose was to examine the relationship among worry about hypoglycemia, diabetes management, and glycemic control within the context of alcohol use, hypoglycemia-related weight control behaviors, depressive symptoms, and impulse control among emerging adults with type 1 diabetes. RESEARCH DESIGN AND METHODS: The sample was 181 emerging adults with type 1 diabetes who were part of a larger study. Path analysis was used to test associations among worry about hypoglycemia, diabetes management, hypoglycemia-related weight control behaviors (WCB), alcohol use, impulse control, depressive symptoms, and glycemic control. RESULTS: Path model fit and modification indices suggested that a feedback loop between worry about hypoglycemia and diabetes management should be incorporated into the original model. Youth with fewer depressive symptoms reported fewer hypoglycemia-related WCB and less worry about hypoglycemia; those with higher impulse control had less alcohol use and better diabetes management; those with lower alcohol use had more worry about hypoglycemia; and better glycemic control was associated with better diabetes management. CONCLUSIONS: Health care professionals need to understand how multiple factors related to worry about hypoglycemia and diabetes management interact in emerging adults. In the context of depressive symptoms, impulse control, alcohol use, and hypoglycemia-related WCB, the path model results suggest several potential avenues for intervening to improve glycemic control in emerging adults

Sleep in children with type 1 diabetes and their parents in the T1D Exchange

Objectives Sleep has physiological and behavioral impacts on diabetes outcomes, yet little is known about the impact of sleep disturbances in children with type 1 diabetes. The current study sought to characterize sleep in children with type 1 diabetes and in their parents and to examine the associations between child sleep, glycemic control and adherence, parent sleep and well-being, parental fear of hypoglycemia, and nocturnal caregiving behavior. Methods Surveys were emailed to parents of 2- to 12-year-old participants in the Type 1 Diabetes (T1D) Exchange clinic registry. Clinical data were obtained from the registry for the 515 respondents. Results In our sample, 67% of children met criteria for poor sleep quality. Child sleep quality was related to glycemic control (HbA1c of 7.9% [63 mmol/mol] in children with poor sleep quality vs 7.6% [60 mmol/mol] in children with non-poor sleep quality; P < 0.001) but not mean frequency of blood glucose monitoring (BGM) (7.6 times/day vs 7.4 in poor/non-poor quality; P = 0.56). Associations were similar for sleep duration. Children with poor sleep quality were more likely to experience severe hypoglycemia (4% in children with poor sleep quality vs 1% in children with non-poor sleep quality; P = 0.05) and more likely to experience DKA (7% vs 4%, respectively; P < 0.001). Poorer child sleep quality was associated with poorer parental sleep quality, parental well-being, and fear of hypoglycemia (P < 0.001 for all). Child sleep was not related to the use of diabetes-related technology (CGM, insulin pump). Conclusions Sleep may be a modifiable factor to improve glycemic control and reduce parental distress

Diabetes-related quality of life and the demands and burdens of diabetes care among emerging adults with type 1 diabetes in the year after high school graduation

The roles of glycemic control, diabetes management, diabetes care responsibility, living independently of parents, and time since high school graduation in predicting diabetes-related quality of life (DQOL) were examined in 184 emerging adults with type 1 diabetes. Data were collected at graduation and 1 year later. Analyses controlling for selected covariates were completed using generalized linear mixed models. Better diabetes management was associated with more positive responses on all four dimensions of DQOL. Impact and worry of DQOL were greater in the presence of depressive symptoms, and life satisfaction was lower. DQOL life satisfaction was lower in those living independently of parents. Young women reported poorer diabetes-related health status than did young men. Time since graduation was not linked to DQOL. Further research is needed on ways to improve DQOL in conjunction with diabetes management and on ways that families can support DQOL when youth live independently

The relationship between BMI and insulin resistance and progression from single to multiple autoantibody positivity and type 1 diabetes among TrialNet Pathway to Prevention participants

Aims/hypothesis The incidence of type 1 diabetes is increasing at a rate of 3–5% per year. Genetics cannot fully account for this trend, suggesting an influence of environmental factors. The accelerator hypothesis proposes an effect of metabolic factors on type 1 diabetes risk. To test this in the TrialNet Pathway to Prevention (PTP) cohort, we analysed the influence of BMI, weight status and insulin resistance on progression from single to multiple islet autoantibodies (Aab) and progression from normoglycaemia to diabetes. Methods HOMA1-IR was used to estimate insulin resistance in Aab-positive PTP participants. Cox proportional hazards models were used to evaluate the effects of BMI, BMI percentile (BMI%), weight status and HOMA1-IR on the progression of autoimmunity or the development of diabetes. Results Data from 1,310 single and 1,897 multiple Aab-positive PTP participants were included. We found no significant relationships between BMI, BMI%, weight status or HOMA1-IR and the progression from one to multiple Aabs. Similarly, among all Aab-positive participants, no significant relationships were found between BMI, weight status or HOMA1-IR and progression to diabetes. Diabetes risk was modestly increased with increasing BMI% among the entire cohort, in obese participants 13–20 years of age and with increasing HOMA1-IR in adult Aab-positive participants. Conclusions/interpretation Analysis of the accelerator hypothesis in the TrialNet PTP cohort does not suggest a broad influence of metabolic variables on diabetes risk. Efforts to identify other potentially modifiable environmental factors should continue

Changes in insulin sensitivity over time and associated factors in HIV-infected adolescents

OBJECTIVE: To compare prevalence of insulin resistance between perinatally HIV-infected (PHIV+) and perinatally HIV-exposed, but uninfected adolescents (PHEU), determine incidence of and contributory factors to new and resolved cases of insulin resistance in PHIV+, and evaluate glucose metabolism. DESIGN: Cross-sectional design for comparison of prevalence among PHIV+ and PHEU. Longitudinal design for incidence and resolution of insulin resistance among PHIV+ at risk for these outcomes. METHODS: The source population was adolescents from pediatric HIV clinics in the United States and Puerto Rico participating in the Pediatric HIV/AIDS Cohort Study, an ongoing prospective cohort study designed to evaluate impact of HIV infection and its treatment on multiple domains in preadolescents and adolescents. Insulin resistance was assessed by homeostatic model assessment of insulin resistance. Those with incident insulin resistance underwent 2-h oral glucose tolerance test and HbA1c. Baseline demographic, metabolic, and HIV-specific variables were evaluated for association with incident or resolved insulin resistance. RESULTS: Unadjusted prevalence of insulin resistance in PHIV+ was 27.3 versus 34.1% in PHEU. After adjustment for Tanner stage, age, sex, and race/ethnicity, there was no significant difference between groups. Factors positively associated with developing insulin resistance included female sex, higher BMI z score, and higher waist circumference; those associated with resolving insulin resistance included male sex and lower BMI z score. CONCLUSION: Prevalence of insulin resistance in PHIV+ and PHEU was substantially higher than that reported in HIV-uninfected nonoverweight youth, but similar to that in HIV-uninfected obese youth. Factors associated with incident or resolved insulin resistance among PHIV+ were similar to those reported in HIV-negative obese youth. However, a contributory role of HIV infection and/or its treatment to the incident risk of insulin resistance cannot be excluded