Glucagon kinetics assessed by mathematical modelling during oral glucose administration in people spanning from normal glucose tolerance to type 2 diabetes

Background/ObjectivesGlucagon is important in the maintenance of glucose homeostasis, with also effects on lipids. In this study, we aimed to apply a recently developed model of glucagon kinetics to determine the sensitivity of glucagon variations (especially, glucagon inhibition) to insulin levels (“alpha-cell insulin sensitivity”), during oral glucose administration.Subjects/MethodsWe studied 50 participants (spanning from normal glucose tolerance to type 2 diabetes) undergoing frequently sampled 5-hr oral glucose tolerance test (OGTT). The alpha-cell insulin sensitivity and the glucagon kinetics were assessed by a mathematical model that we developed previously.ResultsThe alpha-cell insulin sensitivity parameter (named SGLUCA; “GLUCA”: “glucagon”) was remarkably variable among participants (CV=221%). SGLUCA was found inversely correlated with the mean glycemic values, as well as with 2-hr glycemia of the OGTT. When stratifying participants into two groups (normal glucose tolerance, NGT, N=28, and impaired glucose regulation/type 2 diabetes, IGR_T2D, N=22), we found that SGLUCA was lower in the latter (1.50 ± 0.50·10-2vs. 0.26 ± 0.14·10-2 ng·L-1GLUCA/pmol·L-1INS, in NGT and IGR_T2D, respectively, p=0.009; “INS”: “insulin”).ConclusionsThe alpha-cell insulin sensitivity is highly variable among subjects, and it is different in groups at different glucose tolerance. This may be relevant for defining personalized treatment schemes, in terms of dietary prescriptions but also for treatments with glucagon-related agents

The Triglycerides and Glucose (TyG) Index Is Associated with 1-Hour Glucose Levels during an OGTT

Background and Objectives: Among individuals with normal glucose tolerance (NGT), subjects with high levels of plasma glucose (≥155 mg/dL) at sixty minutes during an oral glucose tolerance test (1h-OGTT) are at an increased risk of developing type 2 diabetes. We investigated the association between the triglycerides and glucose (TyG) index, a novel marker of insulin resistance, with 1h-OGTT glucose plasma concentrations. Material and Methods: 1474 non-diabetic Caucasian subjects underwent a 75 g OGTT and were divided into two groups according to the cutoff 1h-OGTT plasma glucose < 155 mg/dL (NGT-1h-low) and ≥ 155 mg/dL (NGT-1h-high). The TyG index was calculated as ln [fasting triglycerides (milligrams per deciliter) × fasting blood glucose (milligrams per deciliter)/2]. Multivariable linear and logistic regression analyses were used to establish the contribution of the TyG index to the variability of 1h-OGTT glucose, and how the former affected the risk of being NGT-1h-high. Results: 1004 individuals were NGT-1h-low and 470 were NGT-1h-high. The TyG index was higher for NGT-1h-high (p = 0.001) individuals, and it was an independent factor influencing 1h-OGTT glycemia (β = 0.191, p < 0.001) after correcting for age, sex, and BMI. The TyG index was the strongest marker associated with the risk of being NGT-1h-high (OR = 1.703, CI 95% 1.34–2.17, p < 0.001) when compared with FPG (OR = 1.054, CI 95% 1.04–1.07, p < 0.001) and the HOMA-IR (OR = 1.156, CI 95% 1.08–1.23, p < 0.001). Conclusions: Our study demonstrated that the TyG index, an efficient and cost-effective marker of insulin resistance, is associated with the variability of early post-challenge glucose levels and is an independent marker of being NGT-1h-high

Metabolic Syndrome Is Associated With Impaired Insulin-Stimulated Myocardial Glucose Metabolic Rate in Individuals With Type 2 Diabetes. A Cardiac Dynamic 18F-FDG-PET Study

Metabolic syndrome is a condition characterized by a clustering of metabolic abnormalities associated with an increased risk of type 2 diabetes and cardiovascular disease. An impaired insulin-stimulated myocardial glucose metabolism has been shown to be a risk factor for the development of cardiovascular disease in patients with type 2 diabetes. Whether cardiac insulin resistance occurs in subjects with metabolic syndrome remains uncertain. To investigate this issue, we evaluated myocardial glucose metabolic rate using cardiac dynamic 18F-FDG-PET combined with euglycemic-hyperinsulinemic clamp in three groups: a group of normal glucose tolerant individuals without metabolic syndrome (n = 10), a group of individuals with type 2 diabetes and metabolic syndrome (n = 19), and a group of subjects with type 2 diabetes without metabolic syndrome (n = 6). After adjusting for age and gender, individuals with type 2 diabetes and metabolic syndrome exhibited a significant reduction in insulin-stimulated myocardial glucose metabolic rate (10.5 ± 9.04 μmol/min/100 g) as compared with both control subjects (32.9 ± 9.7 μmol/min/100 g; P < 0.0001) and subjects with type 2 diabetes without metabolic syndrome (25.15 ± 4.92 μmol/min/100 g; P = 0.01). Conversely, as compared with control subjects (13.01 ± 8.53 mg/min x Kg FFM), both diabetic individuals with metabolic syndrome (3.06 ± 1.7 mg/min × Kg FFM, P = 0.008) and those without metabolic syndrome (2.91 ± 1.54 mg/min × Kg FFM, P = 0.01) exhibited a significant reduction in whole-body insulin-stimulated glucose disposal, while no difference was observed between the 2 groups of subjects with type 2 diabetes with or without metabolic syndrome. Univariate correlations showed that myocardial glucose metabolism was positively correlated with insulin-stimulated glucose disposal (r = 0.488, P = 0.003), and negatively correlated with the presence of metabolic syndrome (r = -0.743, P < 0.0001) and with its individual components. In conclusion, our data suggest that an impaired myocardial glucose metabolism may represent an early cardio-metabolic defect in individuals with the coexistence of type 2 diabetes and metabolic syndrome, regardless of whole-body insulin resistance

Oxygen–Ozone Therapy in Cervicobrachial Pain: A Real-Life Experience

This prospective, open-label clinical study was carried out to evaluate both the efficacy and safety of intramuscular paravertebral injections of an oxygen–ozone (O2–O3) mixture in patients with cervicobrachial pain. We enrolled 540 subjects affected by cervicobrachial pain referred to the Ozone Therapy Ambulatory at the Mater Domini Hospital of Catanzaro (Italy) and to the Center of Pain in Taurianova (Reggio Calabria, Italy). All the subjects (n = 540) completed the treatment and the follow-up visits. The subjects received a mean of 11 cervical intramuscular treatments with an O2–O3 mixture (5 mL) with an O3 concentration of 10 μg/mL bis a week. The improvement of pain was measured by a change in the mean of the Visual Analog Scale (VAS) score from baseline to the end of treatment and during follow-ups. Patient satisfaction was assessed at the end of treatment using the SF-36 Questionnaire. The development of adverse drug reactions was recorded. The mean (±standard deviation) VAS pain score at baseline, at the end of treatment, and during follow-ups showed a significant reduction in pain over time (p p 2–O3 mixture is an effective and safe treatment option for patients with cervicobrachial pain

Vitamin D Serum Levels in Subjects Tested for SARS-CoV-2: What Are the Differences among Acute, Healed, and Negative COVID-19 Patients? A Multicenter Real-Practice Study

Vitamin D might play a role in counteracting COVID-19, albeit strong evidence is still lacking in the literature. The present multicenter real-practice study aimed to evaluate the differences of 25(OH)D3 serum levels in adults tested for SARS-CoV-2 (acute COVID-19 patients, subjects healed from COVID-19, and non-infected ones) recruited over a 6-month period (March–September 2021). In a sample of 117 subjects, a statistically significant difference was found, with acute COVID-19 patients demonstrating the lowest levels of serum 25(OH)D3 (9.63 ± 8.70 ng/mL), significantly lower than values reported by no-COVID-19 patients (15.96 ± 5.99 ng/mL, p = 0.0091) and healed COVID-19 patients (11.52 ± 4.90 ng/mL, p > 0.05). Male gender across the three groups displayed unfluctuating 25(OH)D3 levels, hinting at an inability to ensure adequate levels of the active vitamin D3 form (1α,25(OH)2D3). As a secondary endpoint, we assessed the correlation between serum 25(OH)D3 levels and pro-inflammatory cytokine interleukin-6 (IL-6) in patients with extremely low serum 25(OH)D3 levels (2D3. Although patients with severe hypovitaminosis-D showed no significant increase in IL-6 levels, acute COVID-19 patients manifested high circulating IL-6 at admission (females = 127.64 ± 22.24 pg/mL, males = 139.28 ± 48.95 ng/mL) which dropped drastically after the administration of 1α,25(OH)2D3 (1.84 ± 0.77 pg/mL and 2.65 ± 0.92 ng/mL, respectively). Taken together, these findings suggest that an administration of 1α,25(OH)2D3 might be helpful for treating male patients with an acute COVID-19 infection. Further studies on rapid correction of vitamin D deficiency with fast acting metabolites are warranted in COVID-19 patients

A machine learning approach to predict healthcare-associated infections at intensive care unit admission: findings from the SPIN-UTI project

BACKGROUND: Identifying patients at higher risk of healthcare-associated infections (HAIs) in intensive care unit (ICU) represents a major challenge for public health. Machine learning could improve patient risk stratification and lead to targeted infection prevention and control interventions.AIM: To evaluate the performance of the Simplified Acute Physiology Score (SAPS) II for HAIs risk prediction in ICUs, using both traditional statistical and machine learning approaches.METHODS: We used data of 7827 patients from the "Italian Nosocomial Infections Surveillance in Intensive Care Units" project. The Support Vector Machines (SVM) algorithm was applied to classify patients according to sex, patient origin, non-surgical treatment for acute coronary disease, surgical intervention, SAPS II at admission, presence of invasive devices, trauma, impaired immunity, antibiotic therapy in 48 hours before ICU admission.FINDINGS: The performance of SAPS II for predicting the risk of HAIs provides a ROC (Receiver Operating Characteristics) curve with an AUC (Area Under the Curve) of 0.612 (p<0.001) and an accuracy of 56%. Considering SAPS II along with other characteristics at ICU admission, we found an accuracy of the SVM classifier of 88% and an AUC of 0.90 (p<0.001) for the test set. In line, the predictive ability was lower when considering the same SVM model but removing the SAPS II variable (accuracy= 78% and AUC= 0.66).CONCLUSIONS: Our study suggested the SVM model as a tool to early predict patients at higher risk of HAI at ICU admission