The objective of this study was to evaluate the serum biomarkers implicated in the interaction of platelets and endothelium, as well as the efficacy of antiplatelet therapy in patients with aortic stenosis (AS) and coronary artery disease (CAD). A total of 78 adult patients with CAD on aspirin therapy participated in this study, including 49 consecutive patients with AS and 29 control subjects. The analysis included the following serum biomarkers: thrombomodulin (TM), platelet factor 4 (PF4), P-selectin, and CD40L. The efficacy of antiplatelet treatment was evaluated using the VerifyNow Aspirin test (ASPI test) and P2Y12 assay test (ADP test). Patients with AS exhibited increased serum levels of TM (7.64 ± 3.5 ng/mL vs. 6.28 ± 2.1 ng/mL, p = 0.011) and PF4 (25.16; Q1: 8.3; Q3: 29.6 μg/mL vs. 12.85; Q1: 5.7; Q3: 14.5 μg/mL, p = 0.021) compared to the control group. P-selectin and CD40L levels did not differ between groups. There were no significant differences in platelet aggregation in the ASPI (474.04 ± 66.7 ARU vs. 471.31 ± 56.2 ARU; p = 0.822) or ADP (224.88 ± 46.4 PRU vs. 216.62 ± 29.6 PRU; p = 0.394) tests. Bleeding incidence did not differ significantly between groups. The coexistence of AS in patients with CAD is associated with elevated levels of the aforementioned biomarkers, which are indicative of endothelial damage and platelet activation. However, the efficacy of antiplatelet treatment was independent of the presence of AS.

Background: In recent years, artificial intelligence (AI) methods, including deep convolutional neural networks (CNNs), have gained increasing importance in supporting the automated analysis of echocardiograms. The aim of this study was to evaluate the impact of selected image artifacts—motion blur, acoustic shadowing, and speckle noise—on the performance of automatic classification of standard transthoracic echocardiographic (TTE) views using deep learning models. Methods: The analysis included 217 TTE video clips (2170 frames) covering apical views: two-chamber (A2C), three-chamber (A3C), four-chamber (A4C), and five-chamber (A5C). Two convolutional neural network architectures—ResNet-18 and ResNet-34—were applied, initialized with weights pretrained on the ImageNet dataset (transfer learning). In a limited comparative scope, EfficientNet-B0, a ViT model used as a frozen feature extractor combined with Logistic Regression, and a classical HOG + SVM model, were also included as reference methods. Classification performance was evaluated under conditions of controlled image degradation caused by motion blur, acoustic shadowing, and speckle noise. Results: All analyzed artifacts reduced classification performance, although the magnitude of this effect depended on artifact type. Speckle noise proved to be the most destructive, causing performance collapse across all evaluated methods at high severity. Motion blur and acoustic shadowing produced more differentiated degradation profiles. The ResNet models achieved the highest performance under reference conditions; however, after degradation, the ranking of models was no longer stable. In the comparative analysis, HOG + SVM showed the smallest relative performance loss under motion blur and the highest balanced accuracy under severe acoustic shadowing, whereas severe speckle remained critical for all models. Conclusions: Image quality degradation significantly impairs TTE view classification performance, and evaluation based solely on reference-quality images does not fully reflect model robustness to artifacts. These findings indicate the need to complement standard model evaluation with a structured robustness analysis under degraded imaging conditions and highlight the importance of training and validation settings that better reflect real clinical practice.

The objective of the study was to evaluate the serum biomarkers implicated in the interaction of platelets and endothelium, as well as the efficacy of antiplatelet therapy in patients with aortic stenosis (AS) and coronary artery disease (CAD). A total of 78 adult patients with CAD on aspirin therapy participated in the study, including 49 consecutive patients with AS and 29 control subjects. The analysis included the following serum biomarkers: thrombomodulin (TM), platelet factor 4 (PF4), P-selectin, and CD40L. The efficacy of antiplatelet treatment was evaluated using Verify Now Aspirin (ASPI test) and P2Y12 assay (ADP test). AS patients exhibited increased serum levels of TM (7.64 ± 3.5 ng/mL vs. 6.28 ± 2.1 ng/mL, p = 0.011) and PF4 (25.16 ; Q1:8.3; Q3:29.6 μg/mL vs. 12.85 ; Q1:5.7; Q3:14.5 μg/mL, p = 0.021) compared to the control group. P-selectin and CD40L levels did not differ between groups. There were no differences in platelet aggregation in the ASPI (474.04 ± 66.7 ARU vs. 471.31 ± 56.2 ARU; p = 0.822) or ADP (224.88 ± 46.4 PRU vs. 216.62 ± 29.6 PRU; p = 0.394) tests. Bleeding incidence did not differ significantly between groups. The coexistence of AS in patients with CAD is associated with elevated levels of biomarkers indicative of endothelial damage and platelet activation. However, the efficacy of antiplatelet treatment was independent of the presence of AS.

Background: Diagnostic angiography of coronary arteries is one of the most common procedures in invasive cardiology and is mainly performed via the radial artery. Rapid improvements in the quality of the equipment and operator’s experience have changed the landscape of this procedure. Methods: In this study, 284 patients were analyzed to determine whether heparin administration should be a necessity for all patients to prevent radial artery occlusion (RAO). Moreover, the possible influence of 51 other factors on RAO was analyzed. Results: This study revealed that heparin administration does not have a significant impact on RAO incidence (p = 0.131). However, it was found that a longer fluoroscopy time (p < 0.001) and smaller (5F) vascular sheath (p = 0.001) might serve as protective factors against RAO. On the other hand, a greater number of catheters (p < 0.001), greater compression time (p = 0.001), wider (6F) vascular sheath (p = 0.002), spasm occurrence (p = 0.001), spasmolytic administration (p < 0.001) and atherosclerotic changes in the radial artery (p = 0.005) were risk factors for RAO. Conclusions: This study demonstrates the need for a more personalized approach to the patient when analyzing the individual risk of RAO. In our opinion, it is possible to omit heparin in cases of patients with an initial low risk of RAO or possible adverse drug reactions during diagnostic angiography.