Analysis of differential metabolites in serum metabolomics of patients with aortic dissection.

BACKGROUND: Pathogenesis and diagnostic biomarkers of aortic dissection (AD) can be categorized through the analysis of differential metabolites in serum. Analysis of differential metabolites in serum provides new methods for exploring the early diagnosis and treatment of aortic dissection. OBJECTIVES: This study examined affected metabolic pathways to assess the diagnostic value of metabolomics biomarkers in clients with AD. METHOD: The serum from 30 patients with AD and 30 healthy people was collected. The most diagnostic metabolite markers were determined using metabolomic analysis and related metabolic pathways were explored. RESULTS: In total, 71 differential metabolites were identified. The altered metabolic pathways included reduced phospholipid catabolism and four different metabolites considered of most diagnostic value including N2-gamma-glutamylglutamine, PC(phocholines) (20:4(5Z,8Z,11Z,14Z)/15:0), propionyl carnitine, and taurine. These four predictive metabolic biomarkers accurately classified AD patient and healthy control (HC) samples with an area under the curve (AUC) of 0.9875. Based on the value of the four different metabolites, a formula was created to calculate the risk of aortic dissection. Risk score = (N2-gamma-glutamylglutamine × -0.684) + (PC (20:4(5Z,8Z,11Z,14Z)/15:0) × 0.427) + (propionyl carnitine × 0.523) + (taurine × -1.242). An additional metabolic pathways model related to aortic dissection was explored. CONCLUSION: Metabolomics can assist in investigating the metabolic disorders associated with AD and facilitate a more in-depth search for potential metabolic biomarkers.

Development and validation of a risk prediction model for valve regurgitation in Behçet's disease.

BACKGROUND: In Behçet's disease (BD), mild-to-severe valvular regurgitation (VR) poses a serious complication that contributes significantly to heart failure and eventually death. The accurate prediction of VR is crucial in the early stages of BD subjects for improved prognosis. Accordingly, this study aimed to develop a nomogram that can detect VR early in the course of BD. METHODS: One hundred seventy-two patients diagnosed with Behçet's disease (BD) were conducted to assess cardiac valve regurgitation as the primary outcome. The severity of regurgitation was classified as mild, moderate, or severe. The parameters related to the diagnostic criteria were used to develop model 1. The combination of stepAIC, best subset, and random forest approaches was employed to identify the independent predictors of VR and thus establish model 2 and create a nomogram for predicting the probability of VR in BD. Receiver operating characteristics (ROC) and decision curve analysis (DCA) were used to evaluate the model performance. RESULTS: Thirty-four patients experienced mild-to-severe VR events. Model 2 was established using five variables, including arterial involvement, sex, age at hospitalization, mean arterial pressure, and skin lesions. In comparison with model 1 (0.635, 95% CI: 0.512-0.757), the ROC of model 2 (0.879, 95% CI: 0.793-0.966) was improved significantly. DCA suggested that model 2 was more feasible and clinically applicable than model 1. CONCLUSION: A predictive model and a nomogram for predicting the VR of patients with Behçet's disease were developed. The good performance of this model can help us identify potential high-risk groups for heart failure. Key Points • In this study, the predictors of VR in BD were evaluated, and a risk prediction model was developed for the early prediction of the occurrence of VR in patients with BD. • The VR prediction model included the following indexes: arterial involvement, sex, age at hospitalization, mean arterial pressure, and skin lesions. • The risk model that we developed was better and more optimized than the models built with diagnostic criteria parameters, and visualizing and personalizing the model, a nomogram, provided clinicians with an easy and intuitive tool for practical prediction.

Clinical characteristics and predictors for cardiovascular system involvement in patients with Behçet's disease.

OBJECTIVES: The purpose of this study is to analyse the clinical characteristics of Behçet's disease (BD) patients in China with or without cardiovascular system involvement, and to develop a risk model to identify factors related to cardiovascular involvement in BD. METHODS: This retrospective cohort study, using the information on BD in Shenzhen People's Hospital from January 2000 to December 2021, included 95 patients: BD patients without cardiovascular system involvement (n=63) and with cardiovascular system involvement (n=32). RESULTS: Patients with BD who were males and had a combination of hypertension and a longer duration of disease were more likely to have cardiovascular involvement (p < 0.05). Compared to patients without cardiovascular involvement, manifestations of genital ulcers are rarely observed in those with cardiovascular involvement (60.32% vs. 37.50%, p=0.035). The binary logistic regression analysis found that ascending aortic widening and a history of hypertension were independent risk factors for BD with cardiovascular system involvement (OR=1.277, 95% CI 1.09, 1.495, p=0.002; OR=11.578, 95% CI 1.308, 102.639, p=0.028). The established prediction model indicated that can help to predict the likelihood of cardiovascular involvement in a patient with BD. CONCLUSIONS: Cardiovascular involvement in BD is not at all rare, however, it is often underreported due to a lack of specificity. BD patients who are male, have a history of combined hypertension, and have a long duration of disease should be focused on the presence of combined cardiovascular system involvement, with particular attention to the patient's ascending aortic internal diameter.

Case report: Echocardiographic diagnosis of double orifice mitral valve in an asymptomatic woman.

Double orifice mitral valve (DOMV) is a rare congenital anomaly that is often associated with cardiac malformation. Valve dysfunction usually presents in childhood; therefore, most cases are diagnosed with DOMV in childhood. Its prevalence and prognostic relevance in adulthood are unknown. Here, we report a case of a 38-year-old woman who presented to the outpatient clinic with an abnormal electrocardiogram and was found to have an isolated double orifice mitral valve malformation on transthoracic echocardiography. Echocardiography is the diagnostic tool of choice for patients with double orifice mitral valves. We should familiarize ourselves with the echocardiographic features of DOMV in order to improve the detection.