A Text Messaging Intervention with Financial Incentive for Adolescents with Type 1 Diabetes

2020 ◽  
pp. 193229682095278
Author(s):  
Tara Kaushal ◽  
Lorraine E. Levitt Katz ◽  
Janet Joseph ◽  
Michelle Marowitz ◽  
Knashawn H. Morales ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Financial Incentives ◽  
Text Messaging ◽  
Intervention Group ◽  
Self Care ◽  
Suboptimal Control ◽  
Significant Difference ◽  
The Impact

Background: Adolescents with type 1 diabetes (T1D) have higher hemoglobin A1C (HbA1c) levels than others. In general, adolescents engage with text messaging (TM) and financial incentives, both associated with improved diabetes outcomes. This study aimed to assess the impact of a TM intervention with financial incentives on self-care behaviors and HbA1c. Methods: A six-month randomized controlled trial compared MyDiaText™, a TM education and support application, with standard care. The sample included 166 teens with T1D, 12-18 years old, attending a diabetes clinic. The intervention group received one daily TM and were instructed to respond. Participants who responded to TMs for the most consecutive days were eligible for a financial reward biweekly via lottery. All participants received prompts to complete the self-care inventory (SCI) at baseline, 90, and 180 days. HbA1c was collected at clinic visits. Changes in SCI and HbA1c were analyzed using a multilevel mixed-effects linear regression model. Intention-to-treat and per-protocol analyses were performed. Results: The median TM response rate was 59% (interquartile range 40.1%-85.2%) and decreased over time. After adjustment for baseline characteristics, in per-protocol analysis, there was a statistically significant difference in SCI score increase in those receiving one TM per day vs control ( P = .035). HbA1c decreased overall, without significant difference between groups ( P = .786). Conclusions: A TM intervention with financial incentives for adolescents with T1D in suboptimal control was associated with increasing self-care report; however, glycemic control did not differ from controls. Further research is needed to develop digital health interventions that will impact glycemic control.

scholarly journals Effects of Alternate Insulin Pump Settings in Patients With Type 1 Diabetes During Ramadan: A Randomized Pilot Study

2021 ◽  
pp. 193229682110592
Author(s):  
Ghufran AlGhatam ◽  
Derek O’Keeffe ◽  
Husain Taha
Keyword(s):  
Type 1 Diabetes ◽  
Pilot Study ◽  
Glycemic Control ◽  
Basal Insulin ◽  
Insulin Pump ◽  
Intervention Group ◽  
Control Group ◽  
Insulin Pumps ◽  
Significant Difference

Background: Various studies have evaluated the safety and efficacy of using insulin pumps during Ramadan; some of them demonstrated favorable outcomes in reducing hypoglycemia and hyperglycemia. However, there is no consensus on the recommendations for basal insulin adjustments and the utilization of technical features of insulin pumps to improve glycemic control. Objectives: We aimed to investigate the effects of different insulin pump settings on time in range in patients with type 1 diabetes during Ramadan. Methods: In this randomized pilot study, 30 patients classified to have low to moderate risk for fasting were assigned to either a control group to receive basal insulin adjustments only or an intervention group to use the temporary basal rate and extended bolus features in addition to the basal insulin modifications. The percentage of time spent at different glucose ranges was measured by continuous glucose monitoring. Results: The percentage of time spent within target (70-180 mg/dL) increased significantly in the intervention group from 63.0 ± 10.7 to 76 ± 16.2% (mean difference, 27% points; P < .001). The percentage of time spent in hyperglycemia level 1 (>180 mg/dL) and level 2 (>250 mg/dL) met the criterion of significance, indicating that the intervention group spent less time in hyperglycemia. However, there was no significant difference in the percentage of time spent in hypoglycemia ranges. Conclusions: Incorporating technological approaches of pump therapy with clinical practice guidelines could improve glycemic control during Ramadan.

scholarly journals Impact of Carbohydrate Counting Error on Glycemic Control in Open-Loop Management of Type 1 Diabetes: Quantitative Assessment Through an in silico Trial

2021 ◽  
pp. 193229682110123
Author(s):  
Chiara Roversi ◽  
Martina Vettoretti ◽  
Simone Del Favero ◽  
Andrea Facchinetti ◽  
Pratik Choudhary ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
In Silico ◽  
Open Loop ◽  
Random Errors ◽  
Linear Regression Models ◽  
Reference Case ◽  
Counting Error ◽  
The Impact

Background: In the management of type 1 diabetes (T1D), systematic and random errors in carb-counting can have an adverse effect on glycemic control. In this study, we performed an in silico trial aiming at quantifying the impact of different levels of carb-counting error on glycemic control. Methods: The T1D patient decision simulator was used to simulate 7-day glycemic profiles of 100 adults using open-loop therapy. The simulation was repeated for different values of systematic and random carb-counting errors, generated with Gaussian distribution varying the error mean from -10% to +10% and standard deviation (SD) from 0% to 50%. The effect of the error was evaluated by computing the difference of time inside (∆TIR), above (∆TAR) and below (∆TBR) the target glycemic range (70-180mg/dl) compared to the reference case, that is, absence of error. Finally, 3 linear regression models were developed to mathematically describe how error mean and SD variations result in ∆TIR, ∆TAR, and ∆TBR changes. Results: Random errors globally deteriorate the glycemic control; systematic underestimations lead to, on average, up to 5.2% more TAR than the reference case, while systematic overestimation results in up to 0.8% more TBR. The different time in range metrics were linearly related with error mean and SD ( R2>0.95), with slopes of [Formula: see text], [Formula: see text] for ∆TIR, [Formula: see text], [Formula: see text] for ∆TAR, and [Formula: see text], [Formula: see text] for ∆TBR. Conclusions: The quantification of carb-counting error impact performed in this work may be useful understanding causes of glycemic variability and the impact of possible therapy adjustments or behavior changes in different glucose metrics.

scholarly journals Anxiety, depression, and glycemic control during Covid-19 pandemic in youths with type 1 diabetes

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Maria Cusinato ◽  
Mariangela Martino ◽  
Alex Sartori ◽  
Claudia Gabrielli ◽  
Laura Tassara ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Psychological Impact ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia ◽  
Well Being ◽  
Glucose Variability ◽  
Threshold Score ◽  
The Impact

Abstract Objectives Our study aims to assess the impact of lockdown during the coronavirus disease 2019 pandemic on glycemic control and psychological well-being in youths with type 1 diabetes. Methods We compared glycemic metrics during lockdown with the same period of 2019. The psychological impact was evaluated with the Test of Anxiety and Depression. Results We analyzed metrics of 117 adolescents (87% on Multiple Daily Injections and 100% were flash glucose monitoring/continuous glucose monitoring users). During the lockdown, we observed an increase of the percentage of time in range (TIR) (p<0.001), with a significant reduction of time in moderate (p=0.002), and severe hypoglycemia (p=0.001), as well as the percentage of time in hyperglycemia (p<0.001). Glucose variability did not differ (p=0.863). The glucose management indicator was lower (p=0.001). 7% of youths reached the threshold-score (≥115) for anxiety and 16% for depression. A higher score was associated with lower TIR [p=0.028, p=0.012]. Conclusions Glycemic control improved during the first lockdown period with respect to the previous year. Symptoms of depression and anxiety were associated with worse glycemic control; future researches are necessary to establish if this improvement is transient and if psychological difficulties will increase during the prolonged pandemic situation.

scholarly journals Effect of high-intensity interval training on glycemic control in adults with type 1 diabetes with overweight or obesity: a randomized controlled trial with partial cross-over

2020 ◽  
Author(s):  
Angela S Lee ◽  
Nathan A Johnson ◽  
Margaret McGill ◽  
Jane Overland ◽  
Connie Luo ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
High Intensity ◽  
Intervention Group ◽  
Interval Training ◽  
Control Group ◽  
High Intensity Interval Training ◽  
High Intensity Interval ◽  
Overweight Or Obesity

<b>Objective:</b> To study the effect of 12 weeks of high-intensity interval training (HIIT) on glycemic control in adults with type 1 diabetes with overweight or obesity. <p> </p> <p><b>Research Design and Methods:</b> Thirty inactive adults with type 1 diabetes who had BMI≥25kg/m<sup>2</sup> and HbA1c≥7.5% were randomized to 12 weeks of either: HIIT exercise intervention consisting of 4x4 minutes HIIT (85-95% HRpeak) performed thrice weekly, or usual care control. In a partial cross-over design, the control group subsequently performed the 12-week HIIT intervention. The primary endpoint was the change in HbA1c from baseline to 12 weeks. Glycemic and cardiometabolic outcomes were measured at 0, 12, and 24 weeks.</p> <p> </p> <p><b>Results:</b> Participants were aged 44±10 years, with diabetes duration 19±11 years, and BMI 30.1±3.1 kg/m<sup>2</sup>.<sup> </sup>HbA1c decreased from 8.63 ± 0.66% at baseline to 8.10 ± 1.04% at 12 weeks in the HIIT intervention group (p=0.01), however this change was not significantly different to the control group (HIIT -0.53 ± 0.61%, control -0.14 ± 0.48%, p=0.08). In participants who undertook at least 50% of the prescribed HIIT intervention, the HbA1c reduction was significantly greater than control (HIIT -0.64 ± 0.64% (n=9), control -0.14 ± 0.48% (n=15), p=0.04). There were no differences in insulin dose, hypoglycemia on continuous glucose monitoring, blood pressure, blood lipids, body weight or body composition between groups. </p> <p> </p> <p><b>Conclusions:</b> <a>Overall, there was no significant reduction in HbA1c with a 12-week HIIT intervention in adults with type 1 diabetes. However glycaemic control may improve for people who undertake HIIT with greater adherence.</a></p>

scholarly journals A pilot interventional study to evaluate the impact of cholecalciferol treatment on HbA1c in type 1 diabetes (T1D)

2017 ◽  
Vol 6 (4) ◽  
pp. 225-231 ◽  
Author(s):  
R Perchard ◽  
L Magee ◽  
A Whatmore ◽  
F Ivison ◽  
P Murray ◽  
...  
Keyword(s):  
Vitamin D ◽  
Type 1 Diabetes ◽  
South Asian ◽  
Negative Relationship ◽  
Late Winter ◽  
Vitamin D Levels ◽  
Significant Difference ◽  
Before And After ◽  
The Impact

Background Higher 25(OH)D3 levels are associated with lower HbA1c, but there are limited UK interventional trials assessing the effect of cholecalciferol on HbA1c. Aims (1) To assess the baseline 25(OH)D3 status in a Manchester cohort of children with type 1 diabetes (T1D). (2) To determine the effect of cholecalciferol administration on HbA1c. Methods Children with T1D attending routine clinic appointments over three months in late winter/early spring had blood samples taken with consent. Participants with a 25(OH)D3 level <50 nmol/L were treated with a one-off cholecalciferol dose of 100,000 (2–10 years) or 160,000 (>10 years) units. HbA1c levels before and after treatment were recorded. Results Vitamin D levels were obtained from 51 children. 35 were Caucasian, 11 South Asian and 5 from other ethnic groups. 42 were vitamin D deficient, but 2 were excluded from the analysis. All South Asian children were vitamin D deficient, with mean 25(OH)D3 of 28 nmol/L. In Caucasians, there was a negative relationship between baseline 25(OH)D3 level and HbA1c (r = −0.484, P < 0.01). In treated participants, there was no significant difference in mean HbA1c at 3 months (t = 1.010, P = 0.328) or at 1 year (t = −1.173, P = 0.248) before and after treatment. One-way ANCOVA, controlling for age, gender, ethnicity, BMI and diabetes duration showed no difference in Δ HbA1c level. Conclusion We report important findings at baseline, but in children treated with a stat dose of cholecalciferol, there was no effect on HbA1c. Further studies with larger sample sizes and using maintenance therapy are required.

scholarly journals Association Between Serum Magnesium and Glycemic Control, Lipid Profile and Diabetic Retinopathy in Type 1 Diabetes

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A457-A457
Author(s):  
Isabel Inácio ◽  
Teresa Azevedo ◽  
Sara Ferreira ◽  
Patrícia Rosinha ◽  
Márcia Alves ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Diabetic Retinopathy ◽  
Glycemic Control ◽  
Lipid Profile ◽  
Diabetes Complications ◽  
Serum Magnesium ◽  
Multivariate Logistic Regression Analysis ◽  
Hydroxyvitamin D ◽  
Significant Difference

Abstract Background: Many studies have shown an association between decreased serum magnesium (Mg) levels and poor glycemic control and dyslipidemia in patients with type 1 diabetes (T1DM). However, few studies have evaluated the association between reduced Mg levels and the diabetes complications in these patients and, in particular with diabetic retinopathy (DR), found divergent results. Aims: To evaluate the status of serum Mg levels in adults with T1DM and to assess the association between Mg levels and glycemic control, lipid profile and prevalence of DR. Methods: Retrospective study of adults with T1DM, with an ophthalmological evaluation and a serum Mg level determination. According to Mg levels, the patients were stratified into two groups: normomagnesemic (1.81–2.60 mg/dl) and hypomagnesemic (≤1.80 mg/dl) patients. Exclusion criteria were: patients on diuretics or proton-pump inhibitors, malabsorption or diarrhea, oral magnesium supplementation in recent past, pregnancy or sepsis. Results: Included 105 patients (56.2% male) with median age of 36.0 (interquartile range 16.0) years and median T1DM duration of 16.0 (12.0) years. Median HbA1c was 7.6 (1.5)% and median Mg levels was 1.96 (0.23) mg/dl. Hypomagnesemia (≤1.80 mg/dl) was detected in 20.0% (n=21) patients and 26.7% (n=28) had DR. Hypomagnesemic patients had higher HbA1c [8.2 (1.6) vs 7.5 (1.3)%, p=0.014]. There was no statistical difference in age, sex, T1DM duration or DR between the groups stratified by Mg levels. Mg levels was negatively and weakly correlated with systolic blood pressure (r=-0.200, p=0.041), HbA1c (r=-0.281, p=0.004) and BMI (r=-0.197, p=0.041). There was no correlation between Mg levels and total cholesterol, LDL-C, HDL-C or triglycerides. In multivariate logistic regression analysis, HbA1c was the only predictor of hypomagnesemia [OR=1.541 (1.027–2.312), p=0.037], after the adjustments for age, T1DM duration and BMI. There was no significant difference between patients with or without DR in relation to Mg levels [1.96 (0.28) vs 1.96 (0.19) mg/dL, p=0.986]. Also, there was no statistically significant association between Mg levels and the severity of DR or T1DM duration. In multivariate analysis, T1DM duration, male and estimated glomerular filtration rate &gt;60mL/min/1.73m2 had independently significant association with DR after adjusting for age, glycemic control, hypertension, dyslipidemia, 25-hydroxyvitamin D and Mg levels [OR=1.194 (1.088–1.310), p=&lt;0.001; OR=6.980 (1.654–29.450), p=0.008, and OR=0.780 (0.008–0.751), p=0.028, respectively]. Discussion: Hypomagnesemia is a common problem in adults with T1DM and it was correlated with glycemic control, although we did not find significant association between Mg levels and lipid profile or prevalence of DR. Future longitudinal studies may elucidate the causality between reduced Mg levels and the prevalence of diabetes complications.

scholarly journals Covid Lockdown Impact on Type 1 Diabetes Health and Well-Being

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A338-A338
Author(s):  
Jamie Calma ◽  
Sabrina Sangha ◽  
Marina Basina
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Diabetes Management ◽  
Healthcare Delivery ◽  
Severe Depression ◽  
Well Being ◽  
Depression Symptoms ◽  
Published Data ◽  
The Impact

Abstract Introduction: Data on the impact of the COVID-19 lockdown on glycemic control and psychological well-being in individuals with Type 1 Diabetes Mellitus (T1DM) showed mixed results. Some studies showed improvement in glycemic control attributed to more time for self-care and a more regular lifestyle schedule during the lockdown. However, most published data reflects a short duration of 3–5 months. The impact of long-term social isolation and transition to telemedicine on the health of T1DM patients remains unknown. Our study analyzes patient perception surrounding the impact of an 11-month lockdown on glycemic control, well-being, and self-reported depression symptoms. Methods: PHQ-9 was integrated into a 55-question survey created using RedCap, a secure portal for managing surveys. The survey was sent to 160 T1DM patients over the age of 18 to gauge their current diabetes management and overall well-being prior to, and during the pandemic. The survey also inquired about patients’ perceived effectiveness of telemedicine visits. PHQ9 scores were collected and analyzed along with survey responses. Results: Data collection is still ongoing. From the 47 responders, the PHQ9 screening showed 51% were in the minimal depression score, 34% in the range of mild depression, 11% in moderate depression, and 4% scored in moderate to severe depression. No patients scored within severe depression. In a regular week during the pandemic, 40% of patients experienced difficulty with their motivation and diabetes management and 60% reported no concern, as compared to 36% and 64% respectively before the pandemic. Among the 47 of patient respondents, 30 reported both A1c levels prior and during the pandemic of which 46% showed an improved A1c amid the pandemic, 10% had no change, and 44% reported a worsened A1c level. For the telehealth part of the survey, 90% of patients reported feeling “comfortable with the level of care” they receive via telemedicine, whereas the other 10% were not. Whilst 54% of patients preferred in-person visits and 46% indicated a preference for telehealth visits. Conclusion: T1DM management is challenging. The pandemic adds to the complexity and burden to both self-management and healthcare delivery. Staying locked down for a prolonged period of time imposes economical, psychological, and medical constraints to diabetes care, as nearly half of the patients reported worsening of glycemic control. Our comprehensive survey reports the longest duration reported up to date of how the COVID-19 lockdown impacts patient’s perceived changes in their mental health and diabetes management. It helps clinicians understand the connection between mental and physical health during the pandemic and improve time-restricted telehealth visits by understanding patient concerns. Additional larger scale studies are imperative to expand the knowledge in this field.

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