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 recent decades, it has become clear that the gut is more than just a digestive organ; it also functions as an immune organ with regulatory capabilities and acts as a “second brain” that influences brain function due to the presence and regulatory roles of the gut microbiota (GM). The GM is a crucial component of its host and significantly impacts human health. Dysbiosis, or microbial imbalance, has been closely linked to various diseases, including gastrointestinal, neurological, psychiatric, and metabolic disorders. The aim of this narrative review is to highlight the roles of the GM in maintaining metabolic health. Sleep is a vital biological necessity, with living organisms having evolved an internal sleep–wake rhythm that aligns with a roughly 24 h light/dark cycle, and this is known as the circadian rhythm. This cycle is essential for tissue repair, restoration, and overall optimal body functioning. Sleep irregularities have become more prevalent in modern society, with fast-paced lifestyles often disrupting normal sleep patterns. Urban living factors, such as fast food consumption, shift work, exposure to artificial light and nighttime noise, medications, and social activities, can adversely affect circadian rhythms, with dysbiosis being one of the many factors incriminated in the etiology of sleep disorders.

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.

Recent studies have revealed that dysbiosis, defined as alterations in gut microbiota, plays an important role in the development and the progression of many non-communicable diseases, including metabolic disorders, such as type 2 diabetes mellitus and gestational diabetes mellitus (GDM). The high frequency of GDM makes this disorder an important public health issue, which needs to be addressed in order to reduce both the maternal and fetal complications that are frequently associated with this disease. The studies regarding the connections between gut dysbiosis and GDM are still in their early days, with new research continuously emerging. This narrative review seeks to outline the mechanisms through which a healthy diet that protects the gut microbiota is able to prevent the occurrence of GDM, thus providing medical nutritional therapeutic perspectives for the management of GDM.

Metabolic syndrome (MetS) represents a huge burden on the health system. This study aimed to investigate the association between MetS and certain indirect insulin resistance (IR) indicators according to gender. The triglyceride–glucose index (TyG), TyG–body mass index (TyG–BMI), the TyG–waist-to-height ratio (TyG–WHtR), TyG–waist circumference (TyG–WC), the triglyceride to high-density-lipoprotein cholesterol index (TG/HDL-c) and recently proposed indicators such as the metabolic score for IR (MetS-IR), TyG–neck circumference (TyG–NC) and the TyG–neck-circumference-to-height ratio (TyG–NHtR) were evaluated in 2594 subjects enrolled in the PREDATORR study. Univariate and multivariate logistic regression was performed to identify the association between MetS and the indirect IR indicators, as well as the risk factors. The participants were divided into two groups, according to gender. Data were analyzed using SPSS version 26.0. TyG, TyG–WC, TyG–NC, TyG–NHtR and TG/HDL-c had higher values in the male group, while TyG–BMI, TyG–WHtR and MetS-IR had approximately equal values in the two studied groups, but also statistically significantly higher values in MetS (+) vs. MetS (−) subjects (p < 0.001). For both studied groups, the multivariate logistic regression analysis demonstrated that TyG and MetS-IR were independent predictors for MetS. Both in the female and in the male group, TyG had the largest area under the receiver operating characteristic (AUROC) curve. Thus, in females, the TyG AUROC curve was 0.890; 95% CI 0.873–0.907; p < 0.001; cut-off value 8.51, with 81.4% sensitivity and 80.0% specificity. In males, the TyG AUROC curve was 0.880; 95% CI 0.861–0.899; p < 0.001; cut-off value 8.69, with 78.5% sensitivity and 84.6% specificity. All of the analyzed indirect IR indicators had statistically significantly higher values in MetS (+) vs. MetS (−) subjects. TyG and MetS-IR are independent predictive factors for MetS, regardless of the subject’s gender.

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.