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.

Objective: The objective was to investigate glycemic variability indices in relation to demographic factors and common environmental lifestyles in a general adult population.Methods: The A Estrada Glycation and Inflammation Study is a cross-sectional study covering 1516 participants selected by sampling of the population aged 18 years and over. A subsample of 622 individuals participated in the Glycation project, which included continuous glucose monitoring procedures. Five glycemic variability indices were analyzed, that is, SD, MAGE, MAG, CONGA1, and MODD.Results: Participants had a mean age of 48 years, 62% were females, and 12% had been previously diagnosed with diabetes. In the population without diabetes, index distributions were not normal but skewed to the right. Distributional regression models that adjusted for age, gender, BMI, alcohol intake, smoking status, and physical activity confirmed that all indices were positively and independently associated with fasting glucose levels and negatively with heavy drinking. SD, MAGE, and CONGA1 were positively associated with aging, and MAG was negatively associated with BMI. None of the GVI studied were influenced by physical activity. Age-group-specific reference values are given for the indices.Conclusions: This study yielded age-specific reference values for glucose variability indices in a general adult population. Significant increases were observed with aging. Heavy drinking of more than 140 g/week was associated with significant decreases in variability indices. No differences were found between males and females. These normative ranges provide a guide for clinical care, and may offer an alternative treatment target among persons with diabetes.

Lipodystrophies are a group of diseases mainly characterized by a loss of adipose tissue and frequently associated with insulin resistance, hypertriglyceridemia, and hepatic steatosis. In uncommon lipodystrophies, these complications frequently are difficult to control with conventional therapeutic approaches. This retrospective study addressed the effectiveness of recombinant methionyl leptin (metreleptin) for improving glucose metabolism, lipid profile, and hepatic steatosis in patients with genetic lipodystrophic syndromes. We studied nine patients (five females and four males) with genetic lipodystrophies [seven with Berardinelli-Seip syndrome, one with atypical progeroid syndrome, and one with type 2 familial partial lipodystrophy (FPLD)]. Six patients were children under age 9 years, and all patients had baseline triglycerides levels >2.26 mmol/L and hepatic steatosis; six had poorly controlled diabetes mellitus. Metreleptin was self-administered subcutaneously daily at a final dose that ranged between 0.05 and 0.24 mg/(kg day) [median: 0.08 mg/(kg day)] according to the body weight. The duration of treatment ranged from 9 months to 5 years, 9 months (median: 3 years). Plasma glucose, hemoglobin A1c (Hb A1c), lipid profile, plasma insulin and leptin, and hepatic enzymes were evaluated at baseline and at least every 6 months. Except for the patient with FPLD, metreleptin replacement significantly improved metabolic control (Hb A1c: from 10.4 to 7.1 %, p < 0.05). Plasma triglycerides were reduced 76 % on average, and hepatic enzymes decreased more than 65 %. This study extends knowledge about metreleptin replacement in genetic lipodystrophies, bearing out its effectiveness for long periods of time.

Background: Concerning continuous subcutaneous insulin infusion (CSII), there are controversial results related to changes in glycemic response according to the meal composition and bolus design. Our aim is to determine whether the presence of protein and fat in a meal could involve a different postprandial glycemic response than that obtained with only carbohydrates (CHs). Subjects and Methods: This was a crossover, randomized clinical trial. Seventeen type 1 diabetes (T1D) patients on CSII wore a blinded continuous glucose monitoring system sensor for 3 days. They ingested two meals (meal 1 vs. meal 2) with the same CH content (50 g) but different fat (8.9 g vs. 37.4 g) and protein (3.3 g vs. 28.9 g) contents. A single-wave insulin bolus was used, and the interstitial glucose values were measured every 30 min for 3 h. We evaluated the different postprandial glycemic response between meal 1 and meal 2 by using mixed-effects models. Results: The postmeal glucose increase was 22 mg/dL for meal 1 and 31 mg/dL for meal 2. In univariate analysis, at different times not statistically significant differences in glucose levels between meals occurred. In mixed-model analysis, a time×meal interaction was found, indicating a different response between treatments along the time. However, most of the patients remained in the normoglycemic range (70–180 mg/dL) during the 3-h postmeal period (84.4% for meal 1 and 93.1% for meal 2). Conclusions: The presence of balanced amounts of protein and fat determined a different glycemic response from that obtained with only CH up to 3 h after eating. The clinical relevance of this finding remains to be elucidated.