Insulin resistance (IR) reduces insulin efficacy and heightens the danger of cardiovascular diseases including hypertension. The Metabolic Score for Insulin Resistance (METS-IR), which is based on triglyceride (TG) and high-density lipoprotein cholesterol (HDL-C), body mass index (BMI), and fasting glucose levels, provides a simpler way to assess IR. As the hypertension’s prevalence increases, particularly in those with metabolic disorders, exploring the relationship between hypertension and METS-IR has become crucial. 16,310 individuals from the 2007–2018 National Health and Nutrition Examination Survey dataset was included. Hypertension was defined by asking participants about their medical history and blood pressure measurements. METS-IR was calculated as follows: ln([ HDL-C (mg/dL)] × [2 × fasting glucose (mg/dL)] + TG (mg/dL) × BMI (kg/m2)). The study adjusted for covariates like sex; age; race; poverty-income ratio; marital status; educational background; total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and serum creatinine levels; smoking; stroke; alcohol consumption; diabetes; and coronary heart disease (CHD). This study was conducted using a multi-factor regression model. This research demonstrated a significant positive relationship between hypertension and METS-IR. Each 1-unit rise in METS-IR corresponds to a 3% higher chance of hypertension (odds ratio [OR], 1.03; 95% confidence interval [CI], 1.03–1.04). In model 3, METS-IR exhibited a notable correlation with hypertension (OR, 3.31; 95% CI, 2.64–4.14; P < 0.001). A threshold effect analysis demonstrated a nonlinear association. Finally, subgroup analyses supported the stability of the relationship between METS-IR and factors such as sex, race, alcohol consumption, CHD, smoking, and stroke (P > 0.05). METS-IR showed a strong relationship with hypertension and may be an important marker for evaluating metabolic health and the early hypertension danger.

Dilated cardiomyopathy (DCM) is one of the most common primary myocardial diseases. However, to this day, it remains an enigmatic cardiovascular disease (CVD) characterized by ventricular dilatation, which leads to myocardial contractile dysfunction. It is the most common cause of chronic congestive heart failure and the most frequent indication for heart transplantation in young individuals. Genetics and various other factors play significant roles in the progression of dilated cardiomyopathy, and variants in more than 50 genes have been associated with the disease. However, the etiology of a large number of cases remains elusive. Numerous studies have been conducted on the genetic causes of dilated cardiomyopathy. These genetic studies suggest that mutations in genes for fibronectin, cytoskeletal proteins, and myosin in cardiomyocytes play a key role in the development of DCM. In this review, we provide a comprehensive description of the genetic basis, mechanisms, and research advances in genes that have been strongly associated with DCM based on evidence-based medicine. We also emphasize the important role of gene sequencing in therapy for potential early diagnosis and improved clinical management of DCM.

Objective: Cardiogenic shock seriously affects the survival rate of patients. However, few prognostic models are concerned with the score of cardiogenic shock, and few clinical studies have validated it. In order to optimize the diagnosis and treatment of myocardial infarction complicated with cardiogenic shock and facilitate the classification of clinical trials, the prognosis score model is urgently needed.Methods: Cardiogenic shock, severe case, prognosis score, myocardial infarction and external verification were used as the search terms to search PubMed, Embase, Web of Science, Cochrane, EBSCO (Medline), Scopus, BMC, NCBI, Oxford Academy, Science Direct, and other databases for pertinent studies published up until 1 August 2021. There are no restrictions on publication status and start date. Filter headlines and abstracts to find articles that may be relevant. The list of references for major studies was reviewed to obtain more references.Results and Conclusions: The existing related models are in urgent need of more external clinical verifications. In the meanwhile, with the development of molecular omics and the clinical need for optimal treatment of CS, it is urgent to establish a prognosis model with higher differentiation and coincidence rates.

Background: The non-high-density lipoprotein cholesterol (non-HDL-C)-to-high-density lipoprotein cholesterol (HDL-C) ratio (NHHR) is a strong lipid marker that has been associated with atherogenic features. This study aimed to investigate the potential association between the NHHR and gout prevalence.Methods: This study investigated the relationship between the NHHR and gout by analyzing data gathered from the National Health and Nutrition Examination Survey (NHANES), a research study conducted in the United States from 2007 to 2018. All participants in NHANES provided written informed consent prior to participation. The NHHR was calculated as the ratio of non-HDL-C to HDL-C. Total cholesterol (TC) and HDL-C levels were sourced from NHANES laboratory data. Gout was assessed using a questionnaire. Weighted logistic regression analysis, subgroup analysis, and smoothed curve fitting were performed.Results: This study included 30,482 participants. The fully adjusted models showed that for each unit increase in NHHR in continuous variables, there was a 10% higher likelihood of gout prevalence (OR: 1.10, 95% CI: 1.05, 1.16). Analysis of the NHHR quartiles revealed that patients in the highest quartile had a notably greater probability of developing gout than those in the lowest quartile. (Q4 vs. Q1, OR: 1.34, 95% CI: 1.05, 1.71). Subgroup analyses yielded consistent results across categories, indicating a significant positive association between the NHHR and gout. E-value analysis suggested robustness to unmeasured confounding. Interaction tests showed that the race, education level, marital relationship, poverty-income ratio (PIR), hypertension, smoking habits, estimated glomerular filtration rate (eGFR), lipid-lowering therapy, and diabetes had no discernible effects on this association. The p-values for all the interactions were > 0.05. Nevertheless, the relationship between the NHHR and gout was significantly affected by the age and sex of the participants (interaction p < 0.05).Conclusion: Among adults in the United States, elevated NHHR levels are correlated with increased odds of gout prevalence.