Could Online Education Replace Face-to-Face Education in Diabetes? A Systematic Review.

OBJECTIVE: Diabetes Self-Management Education and Support (DSMES) is a critical component of diabetes care. This study aims to examine the effect of online-based educational interventions on diabetes management compared to face-to-face interventions. METHODS: A systematic review was conducted by searching three databases for studies in English or Spanish between December 2023 and March 2024. The inclusion criteria were studies that compared face-to-face DSMES with online interventions. RESULTS: The follow-up duration of the trials ranged from 1 to 12 months. Multidisciplinary teams delivered online DSMES through various means, including Short Message Service (SMS), telephone calls, video calls, websites, and applications. Online DSMES was found to be comparable to face-to-face interventions in terms of glycated hemoglobin (HbA1c) levels in people with type 1 diabetes (T1D). In contrast, online interventions that focus on weight management in people with type 2 diabetes (T2D) have shown a significant reduction in HbA1c compared to face-to-face interventions. Online DSMES was found to be superior in terms of quality of life and cost-effectiveness in both T1D and T2D. None of the analyzed studies explored the differences between individual and group methodologies. CONCLUSIONS: The current evidence indicates that online DSMES services provide at least comparable biomedical benefits to face-to-face interventions, suggesting that online interventions could be incorporated into clinical practice as a complement or reinforcement. However, further research is needed to explore the potential benefits and effectiveness of online group sessions in DSMES.

A Multicenter Prospective Evaluation of the Benefits of Two Advanced Hybrid Closed-Loop Systems in Glucose Control and Patient-Reported Outcomes in a Real-world Setting.

OBJECTIVE: Advanced hybrid closed-loop systems (AHCL) have been shown to improve glycemic control and patient-reported outcomes in type 1 diabetes. The aim was to analyze the outcomes of two commercially available AHCL in real life. RESEARCH DESIGN AND METHODS: A prospective study was performed, including adolescents and adults with type 1 diabetes, AHCL naïve, from 14 centers, who initiated the use of MM780G with SmartGuard or Tandem t:slimX2 with Control-IQ. Baseline and 3-month evaluations were performed, assessing HbA1c, time in different glycemic ranges, and patient-reported outcomes. The primary outcome was the between-group time in range 70-180 mg/dL difference from beginning to end of follow-up. RESULTS: One hundred fifty participants were included, with 75 initiating each system (age: 39.9 ± 11.4 years [16-72]; 64% female; diabetes duration: 21.6 ± 11.9 years). Time in range increased from 61.53 ± 14.01% to 76.17 ± 9.48% (P < 0.001), with no between-group differences (P = 0.591). HbA1c decreased by 0.56% (95% CI 0.44%, 0.68%) (6 mmol/mol, 95% CI 5, 7) (P < 0.001), from 7.43 ± 1.07% to 6.88 ± 0.60% (58 ± 12 to 52 ± 7 mmol/mol) in the MM780G group, and from 7.14 ± 0.70% to 6.56 ± 0.53% (55 ± 8 to 48 ± 6 mmol/mol) in the Control-IQ group (both P < 0.001 to baseline, P = 0.819 between groups). No superiority of one AHCL over the other regarding fear of hypoglycemia or quality of life was found. Improvement in diabetes-related distress was higher in Control-IQ users (P = 0.012). Sleep quality was improved (PSQI: from 6.94 ± 4.06 to 6.06 ± 4.05, P = 0.004), without differences between systems. Experience with AHCL, evaluated by the INSPIRE measures, exceeded the expectations. CONCLUSIONS: The two AHCL provide significant improvement in glucose control and satisfaction, with no superiority of one AHCL over the other.

The Medtronic 780G advanced hybrid closed-loop system achieves and maintains good glycaemic control in type 1 diabetes adults despite previous treatment.

INTRODUCTION: Improvements in continuous glucose monitoring (CGM) in recent years have changed the treatment of type 1 diabetes (T1D) by permitting the automation of glucose control. The Minimed 780G advanced hybrid closed-loop (ACHL) system adapts basal infusion rates and delivers auto-correction boluses in order to achieve a user-decided glucose target (100, 110 or 120mg/dL). This study set out to evaluate the effectiveness of the Medtronic 780G system in real-life conditions over 6 months. MATERIALS AND METHODS: Prospective study that included T1D subjects previously treated with insulin pump without CGM (pump group) or with sensor-augmented pump with predictive low-glucose suspend (SAP-PLGS group) who started with the Minimed 780G system. Sensor and pump data from baseline, and at 1, 3 and 6 months were downloaded and HbA1c was recorded at baseline and at 6 months. RESULTS: Fifty T1D subjects were included; 25 were previous SAP-PLGS 640G users and 25 used 640G without CGM. 66% were female, 48.6 (40-57) years of age with 20 (12-31.5) years of diabetes duration. Time in range (TIR) improved in the total cohort from baseline to 6 months (69% (57.7-76) vs. 74% (70-82); p=0.01 as did HbA1c (7.6% (7.1-7.8) vs. 7.0% (6.8-7.5); p<0.001), with improvement in times <54, >180 and >250mg/dL. Outcomes at 6 months did not differ between groups, although the SAP-PLGS subjects were prone to hypoglycaemia and the pump group mainly presented suboptimal metabolic control. CONCLUSION: The AHCL Medtronic Minimed 780G system achieves and maintains good glycaemic control over 6 months in real-life conditions in different profiles of T1D subjects.

Role of Excessive Weight Gain During Gestation in the Risk of ADHD in Offspring of Women With Gestational Diabetes.

CONTEXT: Although attention-deficit/hyperactivity disorder (ADHD) has been associated with gestational diabetes mellitus (GDM) and maternal obesity, excessive weight gain (EWG) during pregnancy has scarcely been evaluated. OBJECTIVE: This study aimed to assess the joint effect of maternal weight and EWG on the risk of ADHD in offspring of GDM pregnancies. METHODS: In this cohort study of singleton births >22 weeks of gestation of women with GDM between 1991 and 2008, gestational weight gain above the National Academy of Medicine (NAM) recommendations was classified into EWG. Cox-regression models estimated the effect of maternal pregestational weight and EWG on the risk of ADHD (identified from medical records), adjusted for pregnancy outcomes and GDM-related variables. RESULTS: Of 1036 children who were included, with a median follow-up of 17.7 years, 135 (13%) were diagnosed with ADHD. ADHD rates according to pregestational maternal weight were 1/14 (7.1%) for underweight, 62/546 (11.4%) for normal weight, 40/281 (14.2%) for overweight, and 32/195 (16.4%) for obesity. Only maternal obesity was independently associated with ADHD (HRadjusted 1.66 [95% CI, 1.07-2.60]), but not maternal overweight or EWG. On evaluating the joint contribution of maternal weight and EWG, maternal obesity with EWG was associated with the highest risk of ADHD (vs normal weight without EWG; HRadjusted 2.13 [95% CI, 1.14-4.01]). Pregestational obesity without EWG was no longer associated (HRadjusted 1.36 [95% CI, 0.78-2.36]). CONCLUSION: Among GDM pregnancies, pregestational obesity was associated with a higher risk of ADHD in offspring. Nonetheless, when gestational weight gain was taken into account, only the joint association of obesity and EWG remained significant.

Influence of Maternal Diabetes on the Risk of Neurodevelopmental Disorders in Offspring in the Prenatal and Postnatal Periods.

BACKGROUND: This study aimed to evaluate the influence of maternal diabetes in the risk of neurodevelopmental disorders in offspring in the prenatal and postnatal periods. METHODS: This cohort study included singleton gestational diabetes mellitus (GDM) pregnancies >22 weeks' gestation with live newborns between 1991 and 2008. The control group was randomly selected and matched (1:2) for maternal age, weeks of gestation and birth year. Cox regression models estimated the effect of GDM on the risk of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and maternal type 2 diabetes mellitus (T2DM). Moreover, interaction between maternal T2DM and GDM-ADHD relationship was evaluated. RESULTS: Children (n=3,123) were included (1,073 GDM; 2,050 control group). The median follow-up was 18.2 years (interquartile range, 14.2 to 22.3) (n=323 with ADHD, n=36 with ASD, and n=275 from women who developed T2DM). GDM exposure was associated with ADHD (hazard ratio [HR]crude, 1.67; 95% confidence interval [CI], 1.33 to 2.07) (HRadjusted, 1.64; 95% CI, 1.31 to 2.05). This association remained significant regardless of the treatment (diet or insulin) and diagnosis after 26 weeks of gestation. Children of mothers who developed T2DM presented higher rates of ADHD (14.2 vs. 10%, P=0.029). However, no interaction was found when T2DM was included in the GDM and ADHD models (P>0.05). GDM was not associated with an increased risk of ASD (HRadjusted, 1.46; 95% CI, 0.74 to 2.84). CONCLUSION: Prenatal exposure to GDM increases the risk of ADHD in offspring, regardless of GDM treatment complexity. However, postnatal exposure to maternal T2DM was not related to the development of ADHD.