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Metabolic syndrome (MetS) and its associated cardiometabolic phenotypes significantly contribute to the global burden of cardiovascular disease (CVD), especially in individuals with type 2 diabetes mellitus (T2DM) and prediabetes. This study aimed to explore the association between cardiometabolic phenotypes—specifically, metabolically unhealthy normal weight (MUHNW) and metabolically unhealthy obese (MUHO)—and various cardiovascular risk indices including the triglyceride-glucose (TyG) index and its derivatives, the atherogenic index of plasma (AIP), the cardiometabolic index (CMI), and the cardiac risk ratio (CRR). A total of 300 participants were evaluated (100 with prediabetes and 200 with T2DM). Anthropometric, biochemical, and lifestyle parameters were assessed and stratified across phenotypes. The results demonstrated that cardiovascular risk indices were significantly elevated in the MUHO compared to MUHNW phenotypes, with T2DM patients consistently exhibiting higher risk profiles than their prediabetic counterparts. TyG-derived indices showed strong correlations with BMI, waist–hip ratio (WHR), waist–height ratio (WHtR), and body fat percentage (%BF). The findings suggest that cardiometabolic phenotypes are more strongly associated with elevated cardiometabolic risk indices than body weight alone. These indices may enhance early risk stratification and intervention efforts. The study investigates the association of cardiometabolic phenotypes with surrogate cardiovascular risk indices, not direct CVD outcomes, However, the cross-sectional design and population homogeneity limit the generalizability of the results and preclude causal inference.

Neurotransmitters play a pivotal role not only in central nervous system signaling but also in the regulation of systemic energy metabolism, insulin sensitivity, and cardiovascular function. The contribution of neuroendocrine dysregulation to the development of type 2 diabetes mellitus (T2DM) is increasingly being recognized; however, the interplay between neurotransmitter levels and lipid/insulin resistance profiles in T2DM and prediabetes (PreDM) remains poorly characterized. We evaluated serum dopamine (DA), norepinephrine (NE), epinephrine (EPI), and serotonin (ST) in 110 individuals with PreDM (n = 40) or newly diagnosed T2DM (n = 70). Extended metabolic profiling included HbA1c, lipid panels, and insulin resistance indices (triglyceride-to-glucose index (TyG), TyG-derived indices). Neurotransmitter levels were compared across body mass index (BMI) categories, gender, and glycosylated hemoglobin A1c (HbA1c) quartiles. We applied multivariable linear regression (MLR) adjusted for body mass index (BMI), age, sex, lipids, penalized logistic regression (predicting T2DM status), and exploratory Spearman correlations with False Discovery Rate (FDR) correction. All four neurotransmitters were significantly higher in T2DM versus PreDM (p < 0.001). In T2DM patients, DA and NE levels increased across HbA1c quartiles, and NE levels were significantly higher in quartile 3 compared to quartile 2 (p = 0.045). In multivariable models, T2DM status was the only consistent predictor of neurotransmitter elevations. Logistic regression identified ST (OR = 8.70) and NE (OR = 3.76) as key discriminators of T2DM status, in addition to HbA1c. Exploratory correlation analyses in T2DM showed trends between EPI and insulin resistance indices (TyG adjusted for waist circumference (TyG-WC), TyG adjusted for waist-to-height ratio (TyG-WHtR)) and between DA and low-density lipoprotein cholesterol (LDL-C), although these did not survive to FDR correction. Neurotransmitter levels are elevated in T2DM and correlate with glycemic and metabolic profiles, suggesting early neuroendocrine involvement in the pathogenesis of diabetes. Serotonin and norepinephrine may serve as adjunctive biomarkers for disease stratification, meriting further prospective and mechanistic investigation.

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.

Systemic inflammation has an important role in the prognosis and progression of many chronic diseases, including diabetes (T2DM). This retrospective study aimed to evaluate inflammatory status by determining the serum inflammatory biomarkers (PTX3, hs-CRP, TNF-α, and IL-6) and new indices, like the mean corpuscular volume (MCV) to lymphocyte ratio (MCVL) and cumulative inflammatory index (IIC), in a cohort of patients with prediabetes (PreDM) and newly diagnosed T2DM. We also wanted to assess the association with clinical parameters and different obesity-related indices, to identify possible correlations and to evaluate the diagnostic accuracy of the biomarkers using ROC curve analysis. In this study, we included 60 patients diagnosed with T2DM and 30 patients with PreDM. The ELISA method was applied. Elevated PTX3, hs-CRP, TNF-α, and IL-6 levels were found in T2DM patients compared to preDM patients. An independent relationship was found between PTX3, hs-CRP, and different obesity-related indices in patients with preDM and T2DM. The MCVL index exhibited an inverse trend proportional to the rising levels of HbA1c in the T2DM group. Spearman’s analysis revealed in the T2DM group that the PTX3 values correlated much better with IIC (rho = 0.445, p-value = 0.014) and MCVL (rho = 0.338, p-value = 0.048). Hs-CRP values expressed moderate-to-weak correlations with IIC and MCVL in both groups. Additionally, ROC analysis showed that the PTX3 (AUC was 0.720; p = 0.003; cut-off value 1888.00 pg/mL, with 67.60% sensitivity and 73.30% specificity) and MCVL index (AUC was 0.677; p = 0.047; cut-off value 39.60, with 63.30% sensitivity and 66.70% specificity) have a good, accurate diagnosis compared with IL-6 (AUC was 0.866; p < 0.0001; cut-off value 40.30 pg/mL, with 100.00% sensitivity and 60.00% specificity). IIC showed 61.70% sensitivity and 60.00% specificity, with an AUC of 0.572, p = 0.027 and a cut-off value of 2.35. PTX3 and MCVL can serve as independent predictor factors in the inflammatory status in preDM and T2DM patients, supporting their potential as biomarkers for T2DM management and future research.

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.

Significant gaps remain in the understanding of the etiology and pathogenesis of fibromyalgia (FM), and the COVID-19 pandemic has introduced even more unknowns. Social factors specific to that period, the viral infection itself, and/or vaccination are additional elements that can complicate the progression of the disease or the response to treatment. Aim: The primary hypothesis to be evaluated in this study is that an acute COVID-19 infection, even when considered recovered, may induce changes in the response to non-pharmacological treatment in FM patients, particularly concerning pain. Results: We included 128 patients diagnosed with FM before the pandemic began. The patients were divided based on their history of acute SARS-CoV-2 infection and COVID-19 vaccination status. All patients followed the same rehabilitation program (cognitive therapy, kinesitherapy). Perceived pain: The non-COVID-19 patient groups showed a statistically significant reduction in pain at the final evaluation compared to patients with a history of acute SARS-CoV-2 infection (p < 0.001). Algometric evaluation: Patients without COVID-19 infection and that were vaccinated exhibited the best improvement in pain threshold, both across evaluation times (p < 0.001) and compared to any of the other three groups studied (p < 0.001). Using the WHYMPI questionnaire, the same group of patients (those not having experienced acute COVID-19 and who were vaccinated) was the only group with a statistically significant improvement in pain severity (p = 0.009). In conclusion, to control and improve FM pain symptoms, in addition to appropriate medication, we propose paying additional attention to the history of acute SARS-CoV-2 infection and the COVID-19 vaccination status.

Background/Objectives: Type 2 diabetes mellitus (T2DM), is a rapidly growing global health concern, often accompanied by chronic kidney disease (CKD) and metabolic disturbances. Obesity-related indices, such as the visceral adiposity index (VAI) and body adiposity index (BAI), have been linked to cardiovascular and renal complications in diabetic patients. However, studies integrating both the atherogenic coefficient (AC) and prognostic nutritional index (PNI) for evaluating diabetic nephropathy (DN) remain limited. This study aimed to assess the associations of obesity-related indices with immunological and nutritional factors in patients with T2DM and prediabetes (PreDM). Methods: A retrospective, cross-sectional study was conducted over six months at a university clinical hospital in Dolj County, Romania. The study enrolled 268 newly diagnosed T2DM patients and 150 PreDM patients. Anthropometric parameters, laboratory tests, and demographic data were collected. AC and PNI were calculated using standard formulas, and statistical analyses were performed to determine their associations with metabolic and inflammatory markers. Results: Our study found that T2DM patients had significantly lower PNI values, indicating mild malnutrition, while PreDM patients maintained a normal nutritional status. AC was significantly higher in T2DM patients, correlating with lipid profile alterations and systemic inflammation. Obesity indices, particularly VAI, were significantly elevated in T2DM patients with higher AC values. Statistically significant differences in total cholesterol, low-density lipoprotein cholesterol (LDL-c), and triglycerides were observed between AC subgroups, reinforcing its role in cardiovascular risk assessment. Conclusions: The findings highlight the potential of AC and PNI as biomarkers for assessing nutritional, inflammatory, and lipemic status in diabetic patients. The significant associations between obesity-related indices, lipid profiles, and inflammation markers suggest that early assessment of these parameters may potentially aid in predicting diabetic complications. Further studies are needed to explore the clinical utility of AC and PNI in managing T2DM and CKD progression. Future research should investigate how the lipidic spectrum alters the progression of DN across various patient groups with diabetes and prediabetes

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.

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.