Real-Life Achievements of MiniMed 780G Advanced Closed-Loop System in Youth with Type 1 Diabetes: AWeSoMe Study Group Multicenter Prospective Trial.

Background: We assessed real-life glycemic outcomes and predictors of composite measures of optimal glycemic control in children and adolescents with type 1 diabetes (T1D) during their initial 12 months of the MiniMed™ 780G use. Methods: This prospective observational multicenter study collected demographic, clinical, and 2-week 780G system data at five time points. Optimal glycemic control was defined as a composite glycemic control (CGC) score requiring the attainment of four recommended continuous glucose monitoring (CGM) targets, as well as the glycemia risk index (GRI) of hypoglycemia and hyperglycemia and composite CGM index (COGI). Outcome measures included longitudinal changes in multiple glycemic parameters and CGC, GRI, and COGI scores, as well as predictors of these optimal measures. Results: The cohort included 93 children, 43% girls, with a median age of 15.1 years (interquartile range [IQR] 12.9,17.0). A longitudinal analysis adjusted for age and socioeconomic index yielded a significant improvement in glycemic control for the entire cohort (ptime < 0.001) after the transition to 780G. The mean hemoglobin A1c (HbA1c) (SE) was 8.65% (0.12) at baseline and dropped by >1% after 1 year to 7.54% (0.14) (ptime < 0.001). Optimal glycemic control measures improved at 12 months post 780G; CGC improved by 5.6-fold (P < 0.001) and was attained by 24% of the participants, the GRI score improved by 10-fold (P = 0.009) and was achieved by 10% of them, and the COGI improved by 7.6-fold (P < 0.001) and was attained by 20% of them. Lower baseline HbA1c levels and increased adherence to Advanced Hybrid Closed-Loop (AHCL) usage were predictors of achieving optimal glycemic control. Conclusions: The AHCL 780G system enhances glycemic control in children and adolescents with T1D, demonstrating improvements in HbA1c and CGM metrics, albeit most participants did not achieve optimal glycemic control. This highlights yet ongoing challenges in diabetes management, emphasizing the need for continued proactive efforts on the part of health care professionals, youth, and caregivers.

Virtual reality's impact on children with type 1 diabetes: a proof-of-concept randomized cross-over trial on anxiety, pain, adherence, and glycemic control.

AIMS:  Assess the effectiveness of virtual reality (VR) technology, in reducing pain and anxiety, and improving adherence and glycemic control among children with type 1 diabetes (T1D). METHODS: Children with T1D, managed with continuous glucose monitoring and insulin pumps, were recruited for a randomized cross-over trial. Children were randomized to one of two interventions for diabetes management: group 1 used VR glasses first and group 2 listened to vocal-guided affective imagery first (audio). After 1 month, the interventions were crossed over. The outcome measures included pain and anxiety assessment, adherence, glycemic control, and patient-reported outcome measures (PROMs) of VR satisfaction and effectiveness. RESULTS:  Forty children, mean age 11.4 ± 1.8 years, were participated. During the VR part, the monthly mean pain score compared to the baseline improved in both groups by 30% (p = 0.03). A 14% reduction in the state anxiety score was observed from baseline to 1 month in both groups (p = 0.009). Glycemic control measures including time in range, time above range, and glucose management indicator improved in both groups during VR part (p < 0.004 for all), compared to audio part. After one month, the patient-reported outcome measure (PROM) of satisfaction and effectiveness was sixfold higher after 1 month in group 1 compared to group 2 (p = 0.002). Adherence improved for both groups. CONCLUSIONS: VR was shown to be effective in reducing pain and anxiety, improving adherence, PROM, and glycemic control among children with T1D. We suggest incorporating VR technology in pediatric diabetes clinics to facilitate and improve coping and management of diabetes. TRIAL REGISTRATION: Trial registration number and date of registration for prospectively registered trials:ClinicalTrials.gov Identifier: NCT05883267, May 10th, 2023.

The Mediterranean Diet for Adolescents with Type 1 Diabetes: A Prospective Interventional Study.

The Mediterranean diet (MED) is highly recommended. Medical nutrition therapy is the cornerstone of diabetes treatment. The primary outcome was to evaluate the change in micronutrient intake of youth with type 1 diabetes before and after a 6-month MED intervention; we also assessed adherence and glycemic control. Twenty adolescents, median age 18 years (interquartile range: 15.5-21), median diabetes duration 9 years (7-14), using continuous glucose monitoring devices, received personalized diet regimes based on MED. At 6 months post-intervention, the caloric intake remained unchanged; however, the carbohydrate proportion was lower (p = 0.058), and the intakes of some monounsaturated fats increased (p = 0.049). Sodium intake exceeded the recommended daily allowance by 250% (p = 0.653), before and after the intervention. For blood glucose, the percent TIR (time-in-range, 70-180 mg/dL) improved from 52% (38-60) to 63% (47-71) (p = 0.047). The total insulin dose decreased marginally, from 0.76 u/kg (0.64-0.97) to 0.72 u/kg (0.61-0.89) (p = 0.067). BMI z-score and waist circumference did not change (p = 0.316 and p = 0.161, respectively). Diastolic blood pressure percentile decreased from 73% (68-88) to 69% (50-79) (p = 0.028), and LDL cholesterol from 114 mg/dL (105-134) to 104 mg/dL (96-124) (p = 0.059). The Israeli Mediterranean diet screener score increased, from 8 (7-11) to 13 points (12-14) (p < 0.001). The MED-based intervention in youth with type 1 diabetes is feasible and leads to improvement in monounsaturated fat intake, TIR, and diastolic blood pressure. Other parameters show no change (caloric intake, BMI, and HbA1c).

The Impact of a Low-Carbohydrate Diet on Micronutrient Intake and Status in Adolescents with Type 1 Diabetes.

OBJECTIVE: The aim of this study was to evaluate the macronutrient and micronutrient intake and status in youth with type 1 diabetes mellitus (T1DM) following the consumption of a low-carbohydrate diet (LCD). RESEARCH METHODS AND PROCEDURES: In a prospective intervention clinical trial, adolescents with T1DM using a continuous glucose monitoring device were enrolled. Following a cooking workshop, each participant received a personalized diet regime based on LCD (50-80 g carbohydrate/day). A Food Frequency Questionnaire was administered, and laboratory tests were taken before and 6 months following the intervention. Twenty participants were enrolled. RESULTS: The median age was 17 years (15; 19), and the median diabetes duration was 10 years (8; 12). During the six-months intervention, carbohydrate intake decreased from 266 g (204; 316) to 87 g (68; 95) (p = 0.004). Energy intake, the energy percent from ultra-processed food, and fiber intake decreased (p = 0.001, p = 0.024, and p < 0.0001, respectively). These changes were accompanied by declines in BMI z-score (p = 0.019) and waist-circumference percentile (p = 0.007). Improvement was observed in the median HbA1c from 8.1% (7.5; 9.4) to 7.7% (6.9; 8.2) (p = 0.021). Significant declines below the DRI were shown in median intake levels of iron, calcium, vitamin B1, and folate. CONCLUSIONS: The LCD lowered ultra-processed food consumption, BMI z-scores and the indices of central obesity. However, LCDs require close nutritional monitoring due to the possibility of nutrient deficiencies.

The Gut Microbiome of Adults With Type 1 Diabetes and Its Association With the Host Glycemic Control.

OBJECTIVE: Previous studies have demonstrated an association between gut microbiota composition and type 1 diabetes (T1D) pathogenesis. However, little is known about the composition and function of the gut microbiome in adults with longstanding T1D or its association with host glycemic control. RESEARCH DESIGN AND METHODS: We performed a metagenomic analysis of the gut microbiome obtained from fecal samples of 74 adults with T1D, 14.6 ± 9.6 years following diagnosis, and compared their microbial composition and function to 296 age-matched healthy control subjects (1:4 ratio). We further analyzed the association between microbial taxa and indices of glycemic control derived from continuous glucose monitoring measurements and blood tests and constructed a prediction model that solely takes microbiome features as input to evaluate the discriminative power of microbial composition for distinguishing individuals with T1D from control subjects. RESULTS: Adults with T1D had a distinct microbial signature that separated them from control subjects when using prediction algorithms on held-out subjects (area under the receiver operating characteristic curve = 0.89 ± 0.03). Linear discriminant analysis showed several bacterial species with significantly higher scores in T1D, including Prevotella copri and Eubacterium siraeum, and species with higher scores in control subjects, including Firmicutes bacterium and Faecalibacterium prausnitzii (P < 0.05, false discovery rate corrected for all). On the functional level, several metabolic pathways were significantly lower in adults with T1D. Several bacterial taxa and metabolic pathways were associated with the host's glycemic control. CONCLUSIONS: We identified a distinct gut microbial signature in adults with longstanding T1D and associations between microbial taxa, metabolic pathways, and glycemic control indices. Additional mechanistic studies are needed to identify the role of these bacteria for potential therapeutic strategies.

Prediction of Personal Glycemic Responses to Food for Individuals With Type 1 Diabetes Through Integration of Clinical and Microbial Data.

OBJECTIVE: Despite technological advances, results from various clinical trials have repeatedly shown that many individuals with type 1 diabetes (T1D) do not achieve their glycemic goals. One of the major challenges in disease management is the administration of an accurate amount of insulin for each meal that will match the expected postprandial glycemic response (PPGR). The objective of this study was to develop a prediction model for PPGR in individuals with T1D. RESEARCH DESIGN AND METHODS: We recruited individuals with T1D who were using continuous glucose monitoring and continuous subcutaneous insulin infusion devices simultaneously to a prospective cohort and profiled them for 2 weeks. Participants were asked to report real-time dietary intake using a designated mobile app. We measured their PPGRs and devised machine learning algorithms for PPGR prediction, which integrate glucose measurements, insulin dosages, dietary habits, blood parameters, anthropometrics, exercise, and gut microbiota. Data of the PPGR of 900 healthy individuals to 41,371 meals were also integrated into the model. The performance of the models was evaluated with 10-fold cross validation. RESULTS: A total of 121 individuals with T1D, 75 adults and 46 children, were included in the study. PPGR to 6,377 meals was measured. Our PPGR prediction model substantially outperforms a baseline model with emulation of standard of care (correlation of R = 0.59 compared with R = 0.40 for predicted and observed PPGR respectively; P < 10-10). The model was robust across different subpopulations. Feature attribution analysis revealed that glucose levels at meal initiation, glucose trend 30 min prior to meal, meal carbohydrate content, and meal's carbohydrate-to-fat ratio were the most influential features for the model. CONCLUSIONS: Our model enables a more accurate prediction of PPGR and therefore may allow a better adjustment of the required insulin dosage for meals. It can be further implemented in closed loop systems and may lead to rationally designed nutritional interventions personally tailored for individuals with T1D on the basis of meals with expected low glycemic response.

Obesogenic habits among children and their families in response to initiation of gluten-free diet.

Initiation of a lifelong, gluten-free diet (GFD) in children with celiac disease (CD) influences the child's life in many ways. The aim of this study was to assess the influence of GFD on the child and his/her family's eating habits and lifestyle behaviors. To study this, we asked children and their parents completed the Family Eating and Activity Habits Questionnaire (FEAHQ) at the time of diagnosis of CD and at least 6 months after initiation of GFD and a questionnaires assessing symptoms related to CD and adherence to the GFD diet. We analyzed questionnaires from 40 children with CD and their families. There were 21 females, ranging in age from 4 to 15.7 years (median age 7.4 years±2.8 years). The control group comprised 15 healthy children. After initiation of GFD the family ate more junk food including snacks and candies (p = 0.05), with the significant change reported by children and fathers (p = 0.001 and 0.03 respectively). All family members in the control group had significantly less snacks. Parents and children reported a significant increase in obesogenic eating styles, such as eating from the cooking pot and eating while doing other activities (mothers, p = 0.001; fathers, 0.02; and children, 0.02 respectively). CONCLUSIONS: Our study shows that initiation of GFD in children with CD leads to changes in eating habits and staple food eating that may lead to a more obesogenic environment. Care givers, pediatricians, gastroenterologists, and dieticians alike should be aware of these implications and educate families towards a healthier lifestyle and diet beyond the GFD itself. What's Known: • Gluten-free diet has been shown to affect various psychosocial aspects of children with celiac disease. • Obesity and celiac are associated. What is New: • Initiation of gluten-free diet led to increased eating of junk food both in the patient and his/her family. • After initiation of GFD pro-obesogenic eating habits is increased.