Computerized Automated Reminder Diabetes System (CARDS): E-Mail and SMS Cell Phone Text Messaging Reminders to Support Diabetes Management

Abstract Background: Cell phone text messaging, via the Short Messaging Service (SMS), offers the promise of a highly portable, well-accepted, and inexpensive modality for engaging youth and young adults in the management of their diabetes. This pilot and feasibility study compared two-way SMS cell phone messaging with e-mail reminders that were directed at encouraging blood glucose (BG) monitoring. Methods: Forty insulin-treated adolescents and young adults with diabetes were randomized to receive electronic reminders to check their BG levels via cell phone text messaging or e-mail reminders for a 3-month pilot study. Electronic messages were automatically generated, and participant replies with BG results were processed by the locally developed Computerized Automated Reminder Diabetes System (CARDS). Participants set their schedule for reminders on the secure CARDS website where they could also enter and review BG data. Results: Of the 40 participants, 22 were randomized to receive cell phone text message reminders and 18 to receive e-mail reminders; 18 in the cell phone group and 11 in the e-mail group used the system. Compared to the e-mail group, users in the cell phone group received more reminders (180.4 vs. 106.6 per user) and responded with BG results significantly more often (30.0 vs. 6.9 per user, P = 0.04). During the first month cell phone users submitted twice as many BGs as e-mail users (27.2 vs. 13.8 per user); by month 3, usage waned. Conclusions: Cell phone text messaging to promote BG monitoring is a viable and acceptable option in adolescents and young adults with diabetes. However, maintaining interest levels for prolonged intervals remains a challenge.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78128/1/dia.2008.0022.pd

Coordination of glucose monitoring, self-care behaviour and mental health : achieving precision monitoring in diabetes

Monitoring of glucose plays an essential role in the management of diabetes. However, to fully understand and meaningfully interpret glucose levels, additional information on context is necessary. Important contextual factors include data on behaviours such as eating, exercise, medication-taking and sleep, as well as data on mental health aspects such as stress, affect, diabetes distress and depressive symptoms. This narrative review provides an overview of the current state and future directions of precision monitoring in diabetes. Precision monitoring of glucose has made great progress over the last 5 years with the emergence of continuous glucose monitoring (CGM), automated analysis of new glucose variables and visualisation of CGM data via the ambulatory glucose profile. Interestingly, there has been little progress in the identification of subgroups of people with diabetes based on their glycaemic profile. The integration of behavioural and mental health data could enrich such identification of subgroups to stimulate precision medicine. There are a handful of studies that have used innovative methodology such as ecological momentary assessment to monitor behaviour and mental health in people’s everyday life. These studies indicate the importance of the interplay between behaviour, mental health and glucose. However, automated integration and intelligent interpretation of these data sources are currently not available. Automated integration of behaviour, mental health and glucose could lead to the identification of certain subgroups that, for example, show a strong association between mental health and glucose in contrast to subgroups that show independence of mental health and glucose. This could inform precision diagnostics and precision therapeutics. We identified just-in-time adaptive interventions as a potential means by which precision monitoring could lead to precision therapeutics. Just-in-time adaptive interventions consist of micro-interventions that are triggered in people’s everyday lives when a certain problem is identified using monitored behaviour, mental health and glucose variables. Thus, these micro-interventions are responsive to real-life circumstances and are adaptive to the specific needs of an individual with diabetes. We conclude that, with current developments in big data analysis, there is a huge potential for precision monitoring in diabetes

Depressive symptoms and glycemic control in adolescents with type 1 diabetes

OBJECTIVE—To determine whether the association between depressive symptoms and glycemic control is mediated by blood glucose monitoring (BGM). RESEARCH DESIGN AND METHODS—A total of 276 adolescents with type 1 diabetes (mean age ± SD, 15.6 ± 1.4 years) completed a measure of depressive symptoms. Sociodemographic and family characteristics were obtained from caregivers. BGM frequency and glycemic control were obtained at a clinic visit. RESULTS—Separate regression analyses revealed that depressive symptoms were associated with lower BGM frequency (B = −0.03; P = 0.04) and higher A1C (B = 0.03; P = 0.05) and that lower BGM frequency was associated with higher A1C (B = −0.39; P < 0.001). With depressive symptoms and BGM frequency included together, only BGM frequency was associated with A1C and depressive symptoms became nonsignificant (B = 0.02; P = 0.19). The Sobel test was significant (Z = 1.96; P < 0.05) and showed that 38% of the depression-A1C link can be explained by BGM. CONCLUSIONS—BGM is a mediator between depressive symptoms and glycemic control in adolescents with type 1 diabetes

ACE and non-ACE pathways in the renal vascular response to RAS interruption in type 1 diabetes mellitus

ACE and non-ACE pathways in the renal vascular response to RAS interruption in type 1 diabetes mellitus.BackgroundThe enormous contribution of renin-angiotensin system (RAS) interruption with ACE (angiotensin-converting enzyme) inhibitors and angiotensin II receptor blockers (ARB) in the treatment of diabetic nephropathy has led to interest in the factors involved in angiotensin II (Ang II) generation. In normal subjects, RAS interruption using an ARB produced a 50% greater renal plasma flow (RPF) rise than with an ACE inhibitor, suggesting a substantial contribution of non-ACE pathways. Moreover, immunohistochemistry studies in kidneys of overtly proteinuric diabetic subjects showed up-regulation of chymase, an alternative Ang II-generating enzyme. Our aim was to determine the degree to which the non-ACE pathways contribute to RAS activation in type 1 diabetes mellitus (DM).MethodsType 1DM patients (N = 37, 14 M/23 F; age 31 ± 2 years; DM duration 16 ± 1.7 years; HbA1c 7.7.0 ± 0.3%) were studied on a high-salt diet. They received captopril 25mg po one day and candesartan 16mg po the next day. RPF and glomerular filtration rate (GFR) were measured before and up to 4 hours after drug administration.ResultsBoth captopril and candesartan induced a significant rise in RPF (baseline vs. peak <0.0001 for both), and the rise was concordant for the 2 drugs (r = 0.77,P < 0.001). However, the RPF responses were not significantly different between the 2 drugs (captopril 72 ± 11mL/min/1.73m2, candesartan 75 ± 12,P = 0.841).ConclusionIn predominantly normoalbuminuric, normotensive type 1 DM, activation of the intrarenal RAS reflects a mechanism involving primarily the classic ACE pathway

Transition experiences and health care utilization among young adults with type 1 diabetes

Background: The purpose of this study was to describe the current status of adult diabetes care in young adults with type 1 diabetes and examine associations between health care transition experiences and care utilization. Methods: We developed a survey to assess transition characteristics and current care in young adults with type 1 diabetes. We mailed the survey to the last known address of young adults who had previously received diabetes care at a tertiary pediatric center. Results: Of 291 surveys sent, 83 (29%) were undeliverable and three (1%) were ineligible. Of 205 surveys delivered, 65 were returned (response rate 32%). Respondents (mean age 26.6 ± 3.0 years, 54% male, 91% Caucasian) transitioned to adult diabetes care at a mean age of 19.2 ± 2.8 years. Although 71% felt mostly/completely prepared for transition, only half received recommendations for a specific adult provider. Twenty-six percent reported gaps exceeding six months between pediatric and adult diabetes care. Respondents who made fewer than three diabetes visits in the year prior to transition (odds ratio [OR] 4.5, 95% confidence interval [CI] 1.2–16.5) or cited moving/relocation as the most important reason for transition (OR 6.3, 95% CI 1.3–31.5) were more likely to report gaps in care exceeding six months. Patients receiving current care from an adult endocrinologist (79%) were more likely to report at least two diabetes visits in the past year (OR 6.0, 95% CI 1.5–24.0) compared with those receiving diabetes care from a general internist/adult primary care doctor (17%). Two-thirds (66%) reported receiving all recommended diabetes screening tests in the previous year, with no difference according to provider type. Conclusion: In this sample, transition preparation was variable and one quarter reported gaps in obtaining adult diabetes care. Nevertheless, the majority endorsed currently receiving regular diabetes care, although visit frequency differed by provider type. Because locating patients after transition was incomplete, our findings suggest the need for standardized methods to track transitioning patients

Type 1 Diabetes Through the Life Span: A Position Statement of the American Diabetes Association

Type 1 diabetes is characterized by an immune-mediated depletion of β-cells that results in lifelong dependence on exogenous insulin. While both type 1 and type 2 diabetes result in hyperglycemia, the pathophysiology and etiology of the diseases are distinct and require us to consider each type of diabetes independently. As such, this position statement summarizes available data specific to the comprehensive care of individuals with type 1 diabetes. The goal is to enhance our ability to recognize and manage type 1 diabetes, to prevent its associated complications, and to eventually cure and prevent this disease. The exact number of individuals with type 1 diabetes around the world is not known, but in the U.S., there are estimated to be up to 3 million (1). Although it has long been called “juvenile diabetes” due to the more frequent and relatively straightforward diagnosis in children, the majority of individuals with type 1 diabetes are adults. Most children are referred and treated in tertiary centers, where clinical data are more readily captured. The SEARCH for Diabetes in Youth study estimated that, in 2009, 18,436 U.S. youth were newly diagnosed with type 1 diabetes (12,945 non-Hispanic white, 3,098 Hispanic, 2,070 non-Hispanic black, 276 Asian-Pacific Islander, and 47 American Indian) (2). Worldwide, ∼78,000 youth are diagnosed with type 1 diabetes annually. Incidence varies tremendously among countries: East Asians and American Indians have the lowest incidence rates (0.1–8 per 100,000/year) as compared with the Finnish who have the highest rates (>64.2 per 100,000/year) (3). In the U.S., the number of youth with type 1 diabetes was estimated to be 166,984 (4). The precise incidence of new-onset type 1 diabetes in those over 20 years of age is unknown. This may be due to the prolonged phase of onset and the subtleties in distinguishing the different

Transition to self-management among emerging adults with type 1 diabetes: a mixed methods study

IntroductionEmerging adulthood is challenging for young people with type 1 diabetes (T1D). This study evaluated transition to diabetes self-management and perceptions of care transfer using mixed methods.MethodsAn online survey queried demographics, management characteristics, diabetes knowledge, self-care readiness, adherence, and diabetes distress. T-tests compared survey scores between those with self-reported target A1c &lt;7.0% versus ≥7.0%. Pearson correlations assessed associations between A1c and diabetes distress, stratified by A1c &lt;7.0% versus ≥7.0%. Qualitative semi-structured interviews elicited perceptions of young adults; transcripts were analyzed using directed qualitative content analysis.ResultsOf 141 participants (30% male, 84% non-Hispanic white) completing the survey, 41% self-reported target A1c &lt;7.0%. Diabetes knowledge and self-care readiness scores did not differ between those with A1c &lt;7.0% versus ≥7.0%, while diabetes distress was lower (45 ± 20 vs 52 ± 20, p=0.01) and adherence higher (77 ± 12 vs 71 ± 14, p=0.02) in those with A1c &lt;7.0% versus ≥7.0%. Diabetes distress was significantly associated with glycemic outcomes in those reporting A1c ≥7.0% (R=0.36, p&lt;0.01). Qualitative analysis (24 participants) revealed five themes and two sub-themes, notable for need for more mental health support, support from others with T1D, benefits of technology for care autonomy, and challenges of obtaining diabetes supplies.DiscussionEmerging adults with self-reported target A1c endorsed lower diabetes distress and higher adherence than those with elevated A1c. Mental health access, support from others with T1D, technology use, and guidance for supply acquisition may improve transition to self-management and care transfer for emerging adults with T1D