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Type 2 diabetes disproportionately impacts ethnic minorities and individuals from low socioeconomic status. Diabetes self-management education and support has been shown to improve clinical outcomes in these populations, and mobile health (mHealth) interventions can reduce barriers to access. Dulce Digital-Me (DD-Me) was developed to integrate adaptive mHealth technologies to enhance self-management and reduce disparities in the high-risk, underserved Hispanic population. The objective of the present study was to evaluate reach, adoption, and implementation of an mHealth diabetes self-management education and support intervention in this underrepresented population. The present analysis is a multimethod process evaluation using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. The study was effective in reaching a sample that was representative of the intended population; only modest but significant differences were observed in sex and age. The DD-Me health coach (HC) cited several important facilitators of intervention adoption, including outreach frequency and personalization, and the automated HC report. Implementation fidelity was high, with participants receiving >90% of intended interventions. Participants who received DD-Me with support from a HC were most engaged, suggesting utility and acceptability of integrating HCs with mHealth interventions. Perceptions of implementation among study participants were positive and consistent across study arms. This evaluation revealed the target population was successfully reached and engaged in the digital health interventions, which was implemented with high fidelity. Further studies should evaluate the efficacy and maintenance of the study following the RE-AIM model to determine whether this intervention warrants expansion to additional settings and populations.

BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

BackgroundBy 2034, the number of US individuals with diabetes is predicted to increase from 23.7 to 44.1 million, and annual diabetes-related spending is expected to grow from $113 to $336 billion. Up to 55% of US Hispanics born in the year 2000 are expected to develop diabetes during their lifetime. Poor healthcare access and cultural barriers prevent optimal care, adherence, and clinical benefit, placing Hispanics at disproportionate risk for costly diabetes complications. Mobile technology is increasingly prevalent in all populations and can circumvent such barriers. Our group developed Dulce Digital, an educational text messaging program that improved glycemic control relative to usual care. Dulce Digital-Me (DD-Me) has been tailored to a participant's individual needs with a greater focus on health behavior change.MethodsThis is a three-arm, parallel group, randomized trial with equal allocation ratio enrolling Hispanic adults with low income and poorly managed type 2 diabetes (N = 414) from a San Diego County Federally Qualified Health Center. Participants are randomized to receive Dulce Digital, Dulce Digital-Me-Automated, or Dulce Digital-Me-Telephonic. The DD-Me groups include Dulce Digital components plus personalized goal-setting and feedback delivered via algorithm-driven automated text messaging (DD-Me-Automated) or by the care team health coach (DD-Me-Telephonic) over a 12-month follow-up period. The study will examine the comparative effectiveness of the three groups in improving diabetes clinical control [HbA1c, primary outcome; low-density lipoprotein cholesterol (LDL-C), and systolic blood pressure (SBP)] and patient-provider communication and patient adherence (i.e., medication, self-management tasks) over 12 months and will examine cost-effectiveness of the three interventions.DiscussionOur comparative evaluation of three mHealth approaches will elucidate how technology can be integrated most effectively and efficiently within primary care-based chronic care model approaches to reduce diabetes disparities in Hispanics and will assess two modes of personalized messaging delivery (i.e., automated messaging vs. telephonic by health coach) to inform cost and acceptability.Trial registrationNCT03130699-All items from the WHO Trial Registration data set are available in https://clinicaltrials.gov/ct2/show/study/NCT03130699 .

In the US, nearly 11% of adults were living with diagnosed diabetes in 2017, and significant type 2 diabetes (T2D) disparities are experienced by socioeconomically disadvantaged, racial/ethnic minority populations, including Hispanics. The standard 15-min primary care visit does not allow for the ongoing self-management support that is needed to meet the complex needs of individuals with diabetes. "Team-based" chronic care delivery is an alternative approach that supplements physician care with contact from allied health personnel in the primary care setting (e.g., medical assistants; MAs) who are specially trained to provide ongoing self-management support or "health coaching." While rigorous trials have shown MA health coaching to improve diabetes outcomes, less is known about if and how such a model can be integrated within real world, primary care clinic workflows. Medical Assistant Health Coaching for Type 2 Diabetes in Diverse Primary Care Settings - A Pragmatic, Cluster-Randomized Controlled Trial will address this gap. Specifically, this study compares MA health coaching versus usual care in improving diabetes clinical control among N = 600 at-risk adults with T2D, and is being conducted at four primary care clinics that are part of two health systems that serve large, ethnically/racially, and socioeconomically diverse populations in Southern California. Electronic medical records are used to identify eligible patients at both health systems, and to examine change in clinical control over one year in the overall sample. Changes in behavioral and psychosocial outcomes are being evaluated by telephone assessment in a subset (n = 300) of participants, and rigorous process and cost evaluations will assess potential for sustainability and scalability.

ObjectiveTo determine whether the use of continuous glucose monitoring (CGM) without confirmatory blood glucose monitoring (BGM) measurements is as safe and effective as using CGM adjunctive to BGM in adults with well-controlled type 1 diabetes (T1D).Research design and methodsA randomized noninferiority clinical trial was conducted at 14 sites in the T1D Exchange Clinic Network. Participants were ≥18 years of age (mean 44 ± 14 years), had T1D for ≥1 year (mean duration 24 ± 12 years), used an insulin pump, and had an HbA1c ≤9.0% (≤75 mmol/mL) (mean 7.0 ± 0.7% [53 ± 7.7 mmol/mol]); prestudy, 47% were CGM users. Participants were randomly assigned 2:1 to the CGM-only (n = 149) or CGM+BGM (n = 77) group. The primary outcome was time in range (70-180 mg/dL) over the 26-week trial, with a prespecified noninferiority limit of 7.5%.ResultsCGM use averaged 6.7 ± 0.5 and 6.8 ± 0.4 days/week in the CGM-only and CGM+BGM groups, respectively, over the 26-week trial. BGM tests per day (including the two required daily for CGM calibration) averaged 2.8 ± 0.9 and 5.4 ± 1.4 in the two groups, respectively (P < 0.001). Mean time in 70-180 mg/dL was 63 ± 13% at both baseline and 26 weeks in the CGM-only group and 65 ± 13% and 65 ± 11% in the CGM+BGM group (adjusted difference 0%; one-sided 95% CI -2%). No severe hypoglycemic events occurred in the CGM-only group, and one occurred in the CGM+BGM group.ConclusionsUse of CGM without regular use of confirmatory BGM is as safe and effective as using CGM with BGM in adults with well-controlled T1D at low risk for severe hypoglycemia.

We previously demonstrated that aminoguanidine (AMGN) was able to prevent oxidative modification of LDL. Initially, we thought that this occurred solely because AMGN trapped reactive breakdown products of lipid peroxidation and prevented apoB modification, similar to AMGN's proposed ability to trap reactive glucose intermediates and prevent advanced glycosylation end-product formation. We now demonstrate that AMGN also displays dose-dependent pro-oxidant and antioxidant activity toward LDL. Moderate doses of AMGN (0.05 to 1.0 mmol/L) prevented lipid peroxidation in LDL exposed to copper. AMGN prevented the loss of polyunsaturated fatty acids and delayed or prevented conjugated-diene formation, both of which are sensitive indicators of lipid peroxidation. The same doses of AMGN also prevented apoB modification, a step distal to lipid peroxidation, as evidenced by the ability to (1) prevent fluorescence at 420 nm, (2) block enhanced electrophoretic mobility, and (3) prevent changes leading to enhanced macrophage uptake. Thus, AMGN inhibits LDL modification both by inhibiting lipid peroxidation as well as by trapping reactive breakdown products of lipid peroxidation. It was also demonstrated that for every LDL, there was also a very low dose of AMGN (about 0.01 mmol/L) that actually promoted lipid oxidation and subsequent protein modification. This activity of AMGN could be enhanced by increasing the content of lipid hydroperoxide in the LDL, eg, by aging or radioiodinating the LDL. Conversely, the pro-oxidant activity could be reduced by pretreatment of LDL with ebselen or vitamin E. We propose a mechanism by which AMGN effects pro-oxidant activity toward LDL at very low concentrations and antioxidant activity at higher concentrations and discuss the practical implications of these observations.