Frontiers in Cardiovascular Medicine最新文献

Background: Cardiovascular disease has traditionally been studied predominantly in men, but understanding its manifestations in women is crucial for effective management. This study aims to evaluate the long-term prognosis of female patients with acute coronary syndrome (ACS) within a tertiary hospital setting in Spain.

Methods: Retrospective observational study based on a cohort of consecutive hospitalized patients with ACS from January 2009 to December 2014. Data on demographics, risk factors, treatment, and outcomes were collected, with a median follow-up of 9.2 years.

Results: Women with ACS, constituting 27.3% of 2,330 patients, were older and had a higher prevalence of cardiovascular risk factors such as obesity, hypertension, and diabetes mellitus compared to men. They presented with more non-ST-segment elevation myocardial infarction and underwent less coronary angiography. Female patients were also less likely to be treated with acetylsalicylic acid, a second antiplatelet drug, or statins. Despite initial higher mortality rates [hazard ratio (HR) 1.30; 95% confidence interval (CI) 1.13-1.49; p < 0.001], female patients exhibited a more favorable long-term prognosis after adjustments (adjusted HR 0.82; 95% CI 0.71-0.96; p = 0.014), even in the subgroup analysis excluding patients with unstable angina.

Conclusions: Women with ACS are more comorbid, but after adjustments, female sex appears to be a protective factor that confers a better long-term prognosis.

Aim: Clarify the potential diagnostic value of tongue images for coronary artery disease (CAD), develop a CAD diagnostic model that enhances performance by incorporating tongue image inputs, and provide more reliable evidence for the clinical diagnosis of CAD, offering new biological characterization evidence.

Methods: We recruited 684 patients from four hospitals in China for a cross-sectional study, collecting their baseline information and standardized tongue images to train and validate our CAD diagnostic algorithm. We used DeepLabV3 + for segmentation of the tongue body and employed Resnet-18, pretrained on ImageNet, to extract features from the tongue images. We applied DT (Decision Trees), RF (Random Forest), LR (Logistic Regression), SVM (Support Vector Machine), and XGBoost models, developing CAD diagnostic models with inputs of risk factors alone and then with the additional inclusion of tongue image features. We compared the diagnostic performance of different algorithms using accuracy, precision, recall, F1-score, AUPR, and AUC.

Results: We classified patients with CAD using tongue images and found that this classification criterion was effective (ACC = 0.670, AUC = 0.690, Recall = 0.666). After comparing algorithms such as Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and XGBoost, we ultimately chose XGBoost to develop the CAD diagnosis algorithm. The performance of the CAD diagnosis algorithm developed solely based on risk factors was ACC = 0.730, Precision = 0.811, AUC = 0.763. When tongue features were integrated, the performance of the CAD diagnosis algorithm improved to ACC = 0.760, Precision = 0.773, AUC = 0.786, Recall = 0.850, indicating an enhancement in performance.

Conclusion: The use of tongue images in the diagnosis of CAD is feasible, and the inclusion of these features can enhance the performance of existing CAD diagnosis algorithms. We have customized this novel CAD diagnosis algorithm, which offers the advantages of being noninvasive, simple, and cost-effective. It is suitable for large-scale screening of CAD among hypertensive populations. Tongue image features may emerge as potential biomarkers and new risk indicators for CAD.

Introduction: Human diving reflex is a well-studied phenomenon. However, very little is known about the possible relationship between augmented diving reflex and autonomic dysfunction.

Methods: We retrospectively studied a group of four swimmers who underwent a diving reflex test as part of the examination due to symptoms related to autonomic dysfunction during swimming. The control group comprised 11 healthy swimmers with no history of these symptoms. A standardized diving reflex test was performed for each athlete in both groups. Hemodynamic profiles, including heart rate, stroke volume, and cardiac output, were recorded.

Results: There were no statistically significant differences between the groups in any of the three parameters measured before the test. However, at the end of the test, each parameter (heart rate, stroke volume, and cardiac output) was significantly lower in the swimmers who presented with clinical symptoms related to autonomic dysfunction than in the control group.

Conclusion: This observation could shed light on autonomic dysfunction as a possible cause of sudden cardiac death in swimming athletes. It also demonstrated that autonomic dysfunction is presented not only by decreased heart rate but also by stroke volume, causing a drop in cardiac output to the level of hemodynamic collapse.