Explore the vast range of titles available.

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.

Diabetes mellitus (DM) is a chronic non-communicable disease associated with macroangiopathy and microangiopathy, with disabling or even life-threatening complications. In the present study, we aimed to analyze the association between insulin resistance (IR) and inflammation biomarkers and peripheral arterial disease (PAD) and diabetic peripheral neuropathy (DPN), respectively. The study had a cross-sectional design and evaluated a panel of IR related indices and inflammatory biomarkers commonly used in clinical and epidemiological research, including the triglyceride-glucose (TyG) index and its obesity related derivates, cholesterol, HDL, glucose (CHG) index, lipid-derived ratios, and composite inflammatory indices, together with interleukin-6 (IL-6), tumor necrosis factor alpha (TNFα) and C-reactive protein (CRP) in 110 subjects, according to the presence or absence of PAD and DPN, respectively. In the PAD (+) group, TyG-waist-to-height-ratio (TyG-WHtR) and CHG recorded significantly increased values ( = 0.042, respectively < 0.001), compared to PAD (-). CHG recorded significantly increased values in DPN (+) subjects ( = 0.007). In addition, in the PAD (+) subjects, IL-6 and systemic immune inflammation index (SII) recorded significantly increased values ( = 0.026, respectively, = 0.015) and TNFα, monocyte to lymphocyte ratio (MLR) and C-reactive protein to albumin ratio (CAR) recorded significantly increased values in DPN (+) subjects ( = 0.028, respectively, = 0.008, and = 0.038). We developed a score with a good discriminatory performance for PAD and DPN, including DM duration, TyG-WHtR, SII, MLR and CAR (AUROC 0.822 in PAD, respectively 0.848 in DPN, < 0.001). A composite score combining IR and inflammatory biomarkers showed strong discriminatory performance for lower limb complications in type 2 diabetes, suggesting a valuable tool for early detection and prevention.

Gestational diabetes mellitus (GDM) is a serious and frequent pregnancy complication that can lead to short and long-term risks for both mother and fetus. Different health organizations proposed different algorithms for the screening, diagnosis, and management of GDM. Medical Nutrition Therapy (MNT), together with physical exercise and frequent self-monitoring, represents the milestone for GDM treatment in order to reduce maternal and fetal complications. The pregnant woman should benefit from her family support and make changes in their lifestyles, changes that, in the end, will be beneficial for the whole family. The aim of this manuscript is to review the literature about the Medical Nutrition Therapy in GDM and its crucial role in GDM management.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as one of the greatest challenges for the modern public health system and serves as the foundation for the development of advanced stages, such as metabolic dysfunction-associated steatohepatitis (MASH), which may progress to fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). MASLD and type 2 diabetes mellitus (T2DM) mutually exacerbate one another. MASLD increases the incidence of T2DM and the risk of complications in patients already affected. T2DM accelerates progression to MASH, which has become the second leading cause of liver transplantation and end-stage liver disease, and is associated with hepatic decompensation, cirrhosis, HCC, chronic kidney disease, and cardiovascular disease. MASLD and MASH are strongly linked to T2DM and obesity, pathogenesis including genetic polymorphisms, environmental factors, and multiple metabolic disturbances: insulin resistance (IR), gut dysbiosis, altered adipokine signaling, such as reduced adiponectin alongside increased pro-inflammatory cytokines. Inflammation plays a central role in the development of HCC in MASH, even in the absence of significant fibrosis. The Fibrosis-4 index (FIB-4) should be used as a first-line noninvasive tool to assess fibrosis risk. Additionally, ultrasound-based transient elastography (FibroScan) supports clinicians in assessing steatosis and fibrosis severity. Histologically, MASH is characterized by steatosis, lobular inflammatory changes, and ballooning degeneration of hepatocytes, with or without associated fibrosis. Accurately diagnosing and stratifying MASLD based on fibrosis risk is crucial to identify patients who may benefit from pharmacological treatment or can be managed only with lifestyle interventions. Patients should attain above 10% weight loss through lifestyle modifications. Resmetirom is recommended in F2/F3 fibrosis stages. For treating T2DM, glucagon-like peptide-1 receptor agonists and coagonists, sodium–glucose cotransporter-2 inhibitors, metformin (if glomerular filtration rate exceeds 30 mL/min), and insulin (in decompensated cirrhosis) are preferred. Clinical insights derived from trials are expected to optimize quality of life and long-term outcomes in patients with MASH.

Background and Objectives: Gestational diabetes mellitus (GDM) represents one of the most common complications during pregnancy, being associated with numerous maternal and neonatal complications. The study aimed to analyze maternal and neonatal complications associated with GDM. The risk factors of GDM and of the maternal and neonatal complications were studied in order to prevent their occurrence. Materials and Methods: The study included 97 women in the study, who underwent an oral glucose tolerance test (OGTT) between weeks 24–28 of pregnancy, consequently being divided into two groups: pregnant women with and without GDM. Statistical analysis was performed using the SPSS 26.0 software and MATLAB fitglm, the results being considered statistically significant if p < 0.05. Results: We observed statistically significant differences between the group of women with and without GDM, regarding gestational hypertension (17.6% vs. 0%), preeclampsia (13.72% vs. 0%), and cesarean delivery (96.1% vs. 78,3%). Data on the newborn and neonatal complications: statistically significant differences were recorded between the two groups (GDM vs. no GDM) regarding the average weight at birth (3339.41 ± 658.12 g vs. 3122.83 ± 173.67 g), presence of large for gestational age (21.6% vs. 0%), macrosomia (13.7% vs. 0%), excessive fetal growth (35.3% vs. 0%), respiratory distress (31.4% vs. 0%), hospitalization for at least 24 h in the Neonatal Intensive Care Unit (9.80% vs. 0%), and APGAR score <7 both 1 and 5 min following birth (7.8% vs. 0%). Additionally, the frequency of neonatal hypoglycemia and hyperbilirubinemia was higher among newborns from mothers with GDM. Conclusions: The screening and diagnosis of GDM is vital, and appropriate management is required for the prevention of maternal and neonatal complications associated with GDM. It is also important to know the risk factors for GDM and attempt to prevent their appearance.

Background: Dyslipidemia in pregnancy presents unique clinical challenges due to its effects on maternal and fetal health. This systematic review hypothesizes that molecular alterations in lipid metabolism during pregnancy contribute to adverse pregnancy outcomes and seeks to identify the clinical implications of these changes. The rationale behind this review stems from the increased risk of complications such as preeclampsia, intrauterine growth restriction, and acute pancreatitis associated with dyslipidemia in pregnancy. The primary objective is to examine the interplay between lipid metabolism and pregnancy outcomes. Methods: To achieve this, a systematic review following PRISMA guidelines was conducted, with a comprehensive search of the PubMed database covering articles from January 2014 to June 2024. Inclusion criteria focused on studies assessing molecular alterations and clinical outcomes of dyslipidemia in pregnancy, while case reports and relevant clinical trials were analyzed to evaluate both maternal and fetal outcomes. A total of 12 studies were included in the final analysis. Results: This study provided evidence of the need for early detection and management strategies to reduce risks. The outcomes revealed significant associations between dyslipidemia and adverse maternal outcomes such as preeclampsia, gestational diabetes, and pancreatitis, as well as fetal outcomes like preterm birth and fetal distress. Conclusions: Early lipid monitoring and intervention are crucial in mitigating these risks and suggests that a multidisciplinary approach is necessary to improve maternal and fetal health in pregnancies complicated by dyslipidemia.

In the original publication [...]

Background/Objectives: The prognostic nutritional index (PNI) and Glasgow Prognostic Score (GPS) are associated with patients’ nutritional and immune statuses. One important factor in the pathophysiology of type 2 diabetes mellitus (T2DM) is inflammation. Being present in insulin-target tissues, chronic tissue inflammation has become recognized as a crucial aspect of obesity and type 2 diabetes. This study aimed to compare the PNI and GPS levels of the subjects with T2DM to those of prediabetes (preDM) individuals. Furthermore, the goal was to investigate how these inflammatory markers relate to different types of obesity and whether the combination of PNI, GPS, and obesity-related indices was associated with any particular prognostic variables. Methods: In this study, we enrolled one-hundred patients with newly diagnosed T2DM and one-hundred patients with preDM. Results: Four findings emerged from this observational study. As a first observation, 28% of patients with preDM and 15% of patients with T2DM had a normal weight, while up to 43% of patients with preDM and 60% of patients with T2DM were obese. The second important observation was that the PNI of the T2DM patients was significantly lower than the PNI of the patients with preDM (p < 0.0001). The PNI showed that patients with T2DM had a moderate-to-severe malnutrition status (median value of 38.00). Patients with preDM had a mild-to-moderate malnutrition status (median value of 61.00) at diagnosis. Third, observed in the current study, preDM patients with PNI < 61.00 and T2DM patients with a PNI < 38.00 were associated with significantly higher median values of the waist-to-height ratio (WHtR) (p = 0.041, and p = 0.034, respectively) and body mass index (BMI) (p = 0.016, and p = 0.041, respectively). Fourth, this study also revealed, in the T2DM group, a moderate and statistically significant negative correlation between PNI and weight (rho = −0.322, p = 0.035), waist circumference (WC) (rho = −0.308, p = 0.042), hip circumference (HC) (rho = −0.338, p = 0.039), WHtR (rho = −0.341, p = 0.022), body adiposity index (BAI) (rho = −0.312, p = 0.032), and fasting plasma glucose (FPG) (rho = −0.318, p = 0.029). Additionally, the PNI values expressed a weak negative correlation with BMI (rho = −0.279, p = 0.015), and glycated hemoglobin A1c (HbA1c) (rho = −0.245, p = 0.025). The PNI levels exhibited a single positive correlation, weak but statistically significant, with estimated glomerular filtration rate (eGFR-CKD-EPI) values (rho = 0.263, p = 0.018). Conclusions: The findings of this study regarding the correlations between PNI, GPS, and different obesity-related indices in people with diabetes or prediabetes suggest that these indices, which assess nutritional and inflammatory status, can be used as independent predictor factors associated with the four pillars of DM management (glucose, blood pressure, lipids, and weight control) recommended by the American Diabetes Association (ADA).

Insulin resistance is central in metabolic syndrome, but indices such as Homeostasis Model Assessment-estimated Insulin Resistance (HOMA-IR) require insulin assays that are costly and not always available. Non-insulin-based indices and refined anthropometric markers may offer simpler risk stratification in prediabetes and diabetes. Our objective was to compare insulin and non-insulin-based indices of insulin resistance, together with advanced anthropometric and lipid markers, between prediabetes (PreDM) and type 2 diabetes (T2DM) and across hypertension grades in metabolic syndrome. We conducted a cross-sectional study in 200 adults with metabolic syndrome, 80 with PreDM and 120 with T2DM. Clinical, anthropometric and biochemical parameters were recorded, and HOMA-IR, Homeostasis Model Assessment of Beta-cell function (HOMA%B), Metabolic Score for Insulin Resistance (METS-IR), triglyceride to glucose index (TyG), triglyceride-to-glucose index to high-density lipoprotein cholesterol ratio (TyG/HDL-c) and other derived indices were calculated. Group comparisons, correlations and multiple linear regression were performed. Compared with PreDM, T2DM showed higher glycemic indices and inflammation, but similar body mass index (BMI) and triglycerides. Across glycemic categories and hypertension grades, METS-IR, TyG and TyG/HDL-c increased and correlated strongly with body roundness index (BRI), abdominal volume index (AVI) and weight-adjusted waist index (WWI), while HOMA-IR contributed little independent information. In regression models, lipid adipose product (LAP) and WWI best explained METS-IR in prediabetes, whereas TyG and BRI were the main determinants of METS-IR in diabetes. In metabolic syndrome with PreDM or T2DM, METS-IR and TyG, particularly combined with BRI, AVI and WWI, outperformed traditional lipid ratios and added value beyond HOMA-IR. These composite indices appear useful for insulin resistance assessment when insulin measurement is unavailable or unreliable.

Background: Diabetes mellitus is closely related to periodontal disease and dental lesions, disorders which through dental infection and metabolic imbalance become negatively potentiated and cause a vicious circle that is almost impossible to break. The aim of this research was to study if the severity of dental and periodontal lesions is related to the presence of microvascular complications and glycemic control in patients with type 2 diabetes mellitus (T2DM). Methods: In total, 112 subjects with T2DM that underwent a dental evaluation were enrolled in this case–control study. The study group included 56 patients with complicated lesions, whereas the control group included 56 patients whose gender and age matched the study group and that presented superficial lesions. The statistical analysis was carried out using SPSS 26.0, with the result being considered statistically significant if the p values were <0.05. Results: Statistically significant differences were recorded between the two groups regarding the value of blood glucose, HbA1c and fibrinogen, as well as kidney function. Statistically significant differences were also recorded between the two groups when analyzing the presence of microvascular complications, as well as individually analyzed, in the case of diabetic peripheral sensory-motor neuropathy (p < 0.001), but also of diabetic retinopathy (p < 0.05). This study developed a score with a predictive value for the presence of complicated dental and periodontal lesions, including blood glucose, fibrinogen, diabetic retinopathy, and diabetic peripheral neuropathy (AUROC 0.847, p < 0.001). Conclusions: There is a high frequency of dental and periodontal complications in patients with T2DM. Patients with microvascular complications, elevated fasting blood glucose, and chronic inflammation, as evidenced by elevated fibrinogen, are more likely to develop complicated dental and periodontal lesions.