Purpose: Real-time continuous glucose monitoring (RT-CGM) provides information on glycemic variability (GV), time in range (TIR), and guidance to avoid hypoglycemia, thereby complimenting HbA1c for diabetes management. We investigated whether GV and TIR were independently associated with chronic and acute diabetes complications. Methods: Between September 2014 and January 2017, 515 subjects with type 1 diabetes using sensor-augmented pump therapy were followed for 24 months. The link between baseline HbA1c and CGM-derived glucometrics (TIR [70-180 mg/dL], coefficient of variation [CV], and SD) obtained from the first 2 weeks of RT-CGM use and the presence of complications was investigated. Complications were defined as: composite microvascular complications (presence of neuropathy, retinopathy, or nephropathy), macrovascular complications, and hospitalization for hypoglycemia and/or ketoacidosis. Results: Individuals with microvascular complications were older (P < 0.001), had a longer diabetes duration (P < 0.001), a higher HbA1c (7.8 ± 0.9 vs 7.5 ± 0.9%, P < 0.001), and spent less time in range (60.4 ± 12.2 vs 63.9 ± 13.8%, P = 0.022) compared with those without microvascular complication. Diabetes duration (odds ratio [OR] = 1.12 [1.09-1.15], P < 0.001) and TIR (OR = 0.97 [0.95-0.99], P = 0.005) were independent risk factors for composite microvascular complications, whereas SD and CV were not. Age (OR = 1.08 [1.03-1.14], P = 0.003) and HbA1c (OR = 1.80 [1.02-3.14], P = 0.044) were risk factors for macrovascular complications. TIR (OR = 0.97 [0.95-0.99], P = 0.021) was the only independent risk factor for hospitalizations for hypoglycemia or ketoacidosis. Conclusions: Lower TIR was associated with the presence of composite microvascular complications and with hospitalization for hypoglycemia or ketoacidosis. TIR, SD, and CV were not associated with macrovascular complications.

Background Roux-en-Y gastric bypass (LRYGB) has weight-independent effects on glycemia in obese type 2 diabetic patients, whereas sleeve gastrectomy (LSG) is less well characterized. This study aims to compare early weight-independent and later weight-dependent glycemic effects of LRYGB and LSG. Methods Eighteen LRYGB and 15 LSG patients were included in the study. Glucose, insulin, GLP-1, and GIP levels were monitored during a modified 30 g oral glucose tolerance test before surgery and 2 days, 3 weeks, and 12 months after surgery. Patients self-monitored glucose levels 2 weeks before and after surgery. Results Postoperative fasting blood glucose decreased similarly in both groups (LRYGB vs. SG; baseline—8.1 ± 0.6 vs. 8.2 ± 0.4 mmol/l, 2 days—7.8 ± 0.5 vs. 7.4 ± 0.3 mmol/l, 3 weeks—6.6 ± 0.4 vs. 6.6 ± 0.3 mmol/l, respectively, P < 0.01 vs. baseline for both groups; 12 months—6.6 ± 0.4 vs. 5.9 ± 0.4, respectively, P < 0.05 for LRYGB and P < 0.001 for LSG vs. baseline, P = ns between the groups at all times). LSG, but not LRYGB, showed increased peak insulin levels 2 days postoperatively (mean ± SEM; LSG + 58 ± 14%, P < 0.01; LRYGB − 8 ± 17%, P = ns). GLP-1 levels increased similarly at 2 days, but were higher in LRYGB at 3 weeks (AUC; 7525 ± 1258 vs. 4779 ± 712 pmol × min, respectively, P < 0.05). GIP levels did not differ. Body mass index (BMI) decreased more after LRYGB than LSG (− 10.1 ± 0.9 vs. − 7.9 ± 0.5 kg/m², respectively, P < 0.05). Conclusion LRYGB and LSG show very similar effects on glycemic control, despite lower GLP-1 levels and inferior BMI decrease after LSG.

The epidemiology of non-alcoholic fatty liver disease (NAFLD) in people with type 1 diabetes (T1D) is not yet elucidated. This study aimed to assess the diagnostic accuracy of non-invasive tests for NAFLD, to investigate the prevalence and severity of NAFLD, and to search for factors contributing to NAFLD in people with T1D. In this prospective cohort study, we consecutively screened 530 adults with T1D from a tertiary care hospital, using ultrasound (US), vibration-controlled transient elastography equipped with liver stiffness measurement (LSM) and controlled attenuation parameter, and the fatty liver index. Magnetic resonance spectroscopy (MRS) was performed in a representative subgroup of 132 individuals to validate the diagnostic accuracy of the non-invasive tests. Based on MRS as reference standard, US identified individuals with NAFLD with an AUROC of 0.98 (95% CI 0.95–1.00, sensitivity: 1.00, specificity: 0.96). The controlled attenuation parameter was also accurate with an AUROC of 0.85 (95% CI 0.77–0.93). Youden cut-off was ≥270 dB/m (sensitivity: 0.90, specificity: 0.74). The fatty liver index yielded a similar AUROC of 0.83 (95% CI 0.74–0.91), but the conventional cut-off used to rule in (≥60) had low sensitivity and specificity (0.62, 0.78). The prevalence of NAFLD in the overall cohort was 16.2% based on US. Metabolic syndrome was associated with NAFLD (OR: 2.35 [1.08–5.12], p = 0.031). The overall prevalence of LSM ≥8.0 kPa indicating significant fibrosis was 3.8%, but reached 13.2% in people with NAFLD. NAFLD prevalence in individuals with T1D is 16.2%, with approximately one in 10 featuring elevated LSM. US-based screening could be considered in people with T1D and metabolic syndrome. We aimed to report on the prevalence, disease severity, and risk factors of NAFLD in type 1 diabetes (T1D), while also tackling which non-invasive test for NAFLD is the most accurate. We found that ultrasound is the best test to diagnose NAFLD. NAFLD prevalence is 16.2%, and is associated with metabolic syndrome and BMI. Elevated liver stiffness indicating fibrosis is overall not prevalent in people with T1D (3.8%), but it reaches 13.2% in those with T1D and NAFLD.