The aim of the study was to assess the amount of orally administered carbohydrates needed to maintain euglycemia during moderate-intensity exercise in individuals with type 1 diabetes. Nine participants with type 1 diabetes (four women, age 32.1 ± 9.0 years, BMI 25.5 ± 3.9 kg/m², HbA_1c 55 ± 7 mmol/mol (7.2 ± 0.6%)) on insulin Degludec were randomized to cycle for 55 min at moderate intensity (63 ± 7% VO_2peak) for five consecutive days on either 75% or 100% of their regular basal insulin dose. The impact of pre-exercise blood glucose concentration on the carbohydrate requirement was analyzed by one-way ANOVA stratified for pre-exercise blood glucose quartiles. The effect of the basal insulin dose on the amount of orally administered carbohydrates was evaluated by Wilcoxon matched-pairs signed-rank test. The amount of orally administered carbohydrates during the continuous exercise sessions was similar for both trial arms (75% or 100% basal insulin) with median [IQR] of 36 g (9–62 g) and 36 g (9–66 g) (p = 0.78). The amount of orally administered carbohydrates was determined by pre-exercise blood glucose concentration for both trial arms (p = 0.03). Our study elucidated the importance of pre-exercise glucose concentration related orally administered carbohydrates to maintain euglycemia during exercise in individuals with type 1 diabetes.

Background: In patients with type 2 diabetes mellitus (T2DM) an association between severe hypoglycaemic episodes and the risk of cardiovascular (CV) morbidity and mortality has been previously established. Methods: We aimed to investigate the influence of hypoglycaemia on several diabetes-related and platelet-related miRNAs selected based on bioinformatic analysis and literature search, including hsa-miR-16, hsa-miR-34a, hsa-miR-129-2, hsa-miR-15a, hsa-miR-15b, hsa-miR-106a, miR-223, miR-126. Selected miRNAs were validated by qRT-PCR in 14 patients with T2DM on metformin monotherapy, without established CV disease and antiplatelet therapy during a stepwise hypoglycaemic clamp experiment and a follow-up 7 days after the clamp event. In order to identify which pathways and phenotypes are associated with validated miRNAs we performed target prediction on genes expressed with high confidence in platelets. Results: Circulating levels of miR-106a-5p, miR-15b, miR-15a, miR-16-5p, miR-223 and miR-126 were increased after euglycaemic clamp followed by hypoglycaemic clamp, each with its distinctive time trend. On the contrary, miR-129-2-3p, miR-92a-3p and miR-34a-3p remained unchanged. MiR-16-5p was negatively correlated with interleukin (IL)-6, intercellular adhesion molecule (ICAM) and vascular cell adhesion molecule (VCAM) (p = 0.002, p < 0.001, p = 0.016, respectively), whereas miR-126 was positively correlated with VCAM (p < 0.001). There were negative correlations between miR-16-5p, miR-126 and coagulation factors, including factor VIII and von Willebrand factor (vWF). Among all studied miRNAs, miR-126, miR-129-2-3p and miR-15b showed correlation with platelet function. Bioinformatic analysis of platelet-related targets of analyzed miRNAs showed strong enrichment of IL-2 signaling. We also observed significant enrichment of pathways and diseases related to cancer, CV diseases, hyperglycemia, and neurological diseases. Conclusions: Hypoglycaemia can significantly influence the expression of platelet-enriched miRNAs, with a time trend paralleling the time course of platelet activation. This suggests miRNAs could be exploited as biomarkers for platelet activation in response to hypoglycaemia, as they are probably released by platelets upon activation by hypoglycaemic episodes. Should they hold their promise in clinical endpoint studies, platelet-derived miRNAs might become helpful markers of CV risk in subjects with diabetes. Trial registration The study was registered at clinical trials.gov; Impact of Hypoglycaemia in Patients With DIAbetes Mellitus Type 2 on PLATElet Activation (Diaplate), trial number: NCT03460899

Metabolic regulation of glucose can be altered by fasting periods. We examined glucose metabolism and metabolomics profiles after 12 h and 36 h fasting in non-obese and obese participants and people with type 2 diabetes using oral glucose tolerance (OGTT) and intravenous glucose tolerance testing (IVGTT). Insulin sensitivity was estimated by established indices and mass spectrometric metabolomics was performed on fasting serum samples. Participants had a mean age of 43 ± 16 years (62% women). Fasting levels of glucose, insulin and C-peptide were significantly lower in all cohorts after 36 h compared to 12 h fasting (p < 0.05). In non-obese participants, glucose levels were significantly higher after 36 h compared to 12 h fasting at 120 min of OGTT (109 ± 31 mg/dL vs. 79 ± 18 mg/dL; p = 0.001) but insulin levels were lower after 36 h of fasting at 30 min of OGTT (41.2 ± 34.1 mU/L after 36 h vs. 56.1 ± 29.7 mU/L; p < 0.05). In contrast, no significant differences were observed in obese participants or people with diabetes. Insulin sensitivity improved in all cohorts after 36 h fasting. In line, metabolomics revealed subtle baseline differences and an attenuated metabolic response to fasting in obese participants and people with diabetes. Our data demonstrate an improved insulin sensitivity after 36 h of fasting with higher glucose variations and reduced early insulin response in non-obese people only.

Lipoprotein(a) (Lp(a)) is considered an independent risk factor for cardiovascular diseases. The plasma concentration of Lp(a) is largely genetically determined but varies over a wide range within the population. This study investigated changes in Lp(a) levels after an acute myocardial infarction. Patients who underwent coronary angiography due to an ST elevation myocardial infarction were enrolled (n = 86), and Lp(a) levels were measured immediately after the intervention, one day, two days, and at a post-discharge follow-up visit at 3 to 6 months after the acute myocardial infarction. Median Lp(a) levels increased from a median of 7.9 mg/dL (3.8–37.1) at hospital admission to 8.4 mg/dL (3.9–35.4) on the following day, then to 9.3 mg/dL (3.7–39.1) on day two (p < 0.001), and to 11.2 mg/dL (4.4–59.6) at the post-discharge follow-up (p < 0.001). Lp(a) levels were the lowest during the acute myocardial infarction and started to increase significantly immediately thereafter, with the highest levels at the post-discharge follow-up. The moderate but significant increase in Lp(a) in people with acute myocardial infarction appears to be clinically relevant on an individual basis, especially when specific Lp(a) cut-off levels are supposed to determine the initiation of future treatment. Hence, a repeated measurement of Lp(a) after myocardial infarction should be performed.

The EndoBarrier™ medical device is a duodenal-jejunal bypass liner designed to mimic the effects of gastric bypass surgery to induce weight loss and glycaemic improvement. In this study, 10 participants with type 2 diabetes mellitus (T2DM), a mean body mass index (BMI) of 43.3 ± 5.0 (kg/m²) and a mean glycated haemoglobin A1c (HbA1c) of 60.6 ± 8.6 mmol/mol were examined at baseline (before implantation of EndoBarrier™), 4 weeks after implantation, at 36 weeks (right before explantation) and 24 weeks after the removal of the device to explore the short and long-term effects on glucose metabolism. Besides a significant reduction in body weight and fat mass, EndoBarrier™ treatment significantly improved insulin sensitivity during Botnia clamp investigations after four weeks of implantation. The beneficial effects decreased over time but remained significant 24 weeks after removal of the device.

This study evaluated and compared the performance of simplified acute physiology score 3 (SAPS 3) for predicting in-hospital mortality in COVID-19 patients admitted to intensive care units (ICUs) with and without diabetes in Austria. The Austrian national public health institute (GÖG) data of COVID-19 patients admitted to ICUs (n = 5850) were analyzed. Three versions of SAPS 3 were used: standard equation, Central European equation, and Austrian equation customized for COVID-19 patients. The observed in-hospital mortality was 38.9%, 42.9%, and 37.3% in all, diabetes, and non-diabetes patients, respectively. The overall C-statistics was 0.69 with an insignificant (p = 0.193) difference between diabetes (0.70) and non-diabetes (0.68) patients. The Brier score was > 0.20 for all SAPS 3 equations in all cohorts. Calibration was unsatisfactory for both standard and Central European equations in all cohorts, whereas it was satisfactory for the Austrian equation in diabetes patients only. The SAPS 3 score demonstrated low discrimination and accuracy in Austrian COVID-19 patients, with an insignificant difference between diabetes and non-diabetes. All equations were miscalibrated particularly in non-diabetes patients, while the Austrian equation showed satisfactory calibration in diabetes patients only. Both uncalibrated and calibrated versions of SAPS 3 should be used with caution in COVID-19 patients.