Coenzyme Q10 (CoQ10) is a natural compound with potent antioxidant properties. Its provision through diet does not always allow adequate levels in the human body, and supplementation is often necessary. This bioavailability study intended to explore the plasma concentration levels of a novel CoQ10 oral preparation (COQUN^®, Coenzyme Q10 Miniactives Retard 100 mg capsules) mimicking assumption on a regular basis. Twenty-four healthy adults tested a single dose of CoQ10 100 mg in one day to assess bioavailability. After a one week wash-out period, they were randomly assigned (1:1) to continuous administration for four weeks: Group A (n = 12) 100 mg once a day (OD); and Group B (n = 12) 100 mg twice a day (BID). During the single dose phase, C_max was observed at 4 h, and the mean values of AUC_t and T_max were 8754 μg/mL·h and 4.29 h, respectively. The multiple dose phase showed increasing plasma levels up to 7 days after the start of administration, and sustained high concentrations during the all administration period. No relevant adverse events were reported. These results show that Miniactives^® technology can release CoQ10 to allow high constant blood concentrations without a sharp decrease. This may be the first step of evidence for a potential new antioxidative treatment in human chronic diseases deserving high CoQ10 levels.

Optimal glycemic control without the presence of diabetes-related complications is the primary goal for adequate diabetes management. Recent studies have shown that hemoglobin A1c level cannot fully evaluate diabetes management as glycemic fluctuations are demonstrated to have a major impact on the occurrence of diabetes-related micro- and macroangiopathic comorbidities. The use of continuous glycemic monitoring systems allowed the quantification of glycemic fluctuations, providing valuable information about the patients’ glycemic control through various indicators that evaluate the magnitude of glycemic fluctuations in different time intervals. This review highlights the significance of glycemic variability by describing and providing a better understanding of common and alternative indicators available for use in clinical practice.

Diabetes mellitus (DM) is a complex chronic disease, with a prevalence that has reached alarming proportions in recent decades. In this study, we aimed to analyze the association of type 2 diabetes mellitus (T2DM) with certain insulin resistance (IR) indicators, according to the gender of the participants enrolled in the PREDATORR study. Biomarkers such as the triglyceride–glucose (TyG) index and its derivates, triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-c), and metabolic score for insulin resistance (METS-IR), as well as recent indicators, like cholesterol, HDL, the glucose (CHG) index and its derivates, CHG–body mass index (CHG-BMI), and CHG–waist circumference (CHG-WC), as well as its newly proposed derivates, such as CHG–waist-to-height ratio (CHG-WHtR), CHG–neck circumference (CHG-NC), and CHG–neck-to-height ratio (NHtRs were analyzed in 2080 subjects, divided into two groups, according to gender). Univariate and multivariate logistic regression was used to identify the relationships between IR indicators and T2DM. Regardless of gender, all the analyzed indicators presented statistically significantly higher values in T2DM (+) compared to T2DM (−). For both studied groups, CHG–WHtR had the largest AUROC curve: in males, the AUROC curve was 0.809, the cut-off value being 3.22, with a 70.7% sensitivity and 75.3% specificity; in females, the AUROC curve was 0.840, the cut-off value was 3.20, with a 79.3% sensitivity and 75.5% specificity, respectively. Regardless of gender, the age-adjusted model for multivariate logistic regression analysis demonstrated that TyG and CHG were predictive factors for T2DM.

Background: Glycemic variability (GV) is a novel parameter used in evaluating the quality of diabetes management. Current guidelines recommend the use of GV indexes alongside the traditional parameter to evaluate glycemic control: hemoglobin A1c (HbA1c). This study aims to evaluate the extent to which HbA1c explains the GV phenomena in patients with Type 1 diabetes (T1DM). Methods: In 147 patients with T1DM, associations between HbA1c and several GV indexes were analyzed. Results: Patients with an HbA1c < 7% had a lower median standard deviation of glycemia (60 vs. 48; p < 0.001), a lower coefficient of variation (34.1 vs. 38.0; p < 0.001), and a significantly increased median time in range (78 vs. 58; p < 0.001). HbA1c was positively correlated with the coefficient of variation (r = 0.349; p < 0.001) and the standard deviation (r = 0.656; p < 0.001) but reversely correlated with a lower time in range (r = −0.637; p < 0.001). Conclusions: HbA1c only partially explains the GV phenomena in patients with T1DM. The HbA1c value is associated more strongly with the time in range and standard deviation than with the coefficient of variation.

Introduction: Type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) share a bidirectional link, and the innovative antidiabetic molecules GLP-1 Ras and SGLT-2is have proven cardiac and renal benefits, respectively. This study aimed to evaluate CV risk categories, along with lipid-lowering and antidiabetic treatments, in patients with T2DM from a real-life setting in Romania. Material and Methods: A cross-sectional evaluation was conducted on 405 consecutively admitted patients with T2DM in an ambulatory setting, assessing them according to the 2019 ESC/EAS guidelines for moderate, high, and very high CV risk categories. Results: The average age of the group was 58 ± 9.96 years, with 38.5% being female. The mean HbA1C level was 7.2 ± 1.7%. Comorbidities included HBP in 88.1% of patients, with a mean SBP and DBP of 133.2 ± 13.7 mm Hg and 79.9 ± 9 mm Hg, respectively, and obesity in 66.41%, with a mean BMI of 33 ± 6.33 kg/m². The mean LDL-C levels varied by CV risk category: 90.1 ± 34.22 mg/dL in very high risk, 98.63 ± 33.26 mg/dL in high risk, and 105 ± 37.1 mg/dL in moderate risk. Prescribed treatments included metformin (100%), statins (77.5%), GLP-1 Ras (29.4%), and SGLT-2is (29.4%). Conclusions: In Romania, patients with T2DM often achieve glycemic control targets but fail to meet composite targets that include glycemic, BP, and lipid control. Additionally, few patients benefit from innovative glucose-lowering therapies with proven cardio-renal benefits or from statins.

Background: Individuals diagnosed with type 2 diabetes mellitus (T2DM) are more prone to experiencing severe cardiovascular (CV) events, often occurring at a younger age, due to a complex interplay of risk factors. T2DM diagnosis inherently classifies patients as belonging to a higher CV risk group. In light of the increased susceptibility to severe CV outcomes, our study aims to assess the distribution of CV risk categories and the attainment of therapeutic targets among Romanian patients diagnosed with T2DM. Methods: A cross-sectional analysis was performed, including 885 patients diagnosed with T2DM who were consecutively admitted to a secondary care hospital unit between January and July 2019. Data collection included demographics, lipid profile, glycated hemoglobin (HbA1c), blood pressure (BP), estimated glomerular filtration rate (eGFR), and medication specifics for T2DM and associated conditions. Patients were stratified into CV risk categories based on the ESC/EAS guidelines, encompassing moderate, high, and very high risk categories. The rationale for selecting these guidelines for CV risk categories was that they were current and provided best practice recommendations for T2DM patients during the cross-sectional evaluation. We assessed therapeutic target achievement rates for LDL-C, HbA1C, and BP for each CV risk category. Additionally, we examined utilization rates of statins and novel cardio- and reno-protective, non-insulin antidiabetic medications. Results: The group’s average age was 62.9 ± 7.7 years and comprised 53.7% females. An average HbA1c level of 7.1 ± 1.3% was observed in the group. Within the cohort, 83% had hypertension, with a mean systolic BP of 132 ± 16.2 mm Hg and mean diastolic BP of 80 ± 9.6 mm Hg. Additionally, 64.6% of patients were obese, with a mean body mass index of 32.3 ± 5.3 kg/m². Mean LDL-C levels varied across the different CV risk categories: 106.6 ± 35.6 mg/dL in the very high risk category, 113 ± 39.3 mg/dL in the high risk category, and 124.3 ± 38.3 mg/dL in the moderate risk category. Most treatment schemes included metformin (87.0%) and statins (67.0%), with variable use rates for other glucose-lowering and CV risk-modifying therapies. The percentage of patients using GLP-1 RAs was 8.1%, while 3.9% used SGLT2 inhibitors. Conclusions: Most Romanian patients with T2DM are at very high or high CV risk. Despite reaching glycemic control targets, most patients are not achieving the composite target, which includes, besides glycemic control, BP values and lipid profile. Many patients with T2DM are not benefiting from DM therapies with additional cardiorenal benefits or statins.