Background: This study aims to compare the performance of machine learning (ML) models developed to predict long-term mortality risk in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (pPCI) and to investigate the prognostic value of novel inflammatory–metabolic indices. Methods: In this retrospective study, 329 consecutive STEMI patients who underwent pPCI (292 survivors, 37 deaths) were included. Five ML algorithms—Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Artificial Neural Networks (ANN)—were developed for mortality prediction. Model performance was evaluated using accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC). SHAP (Shapley Additive exPlanations) analysis was used to interpret model decision mechanisms. Results: The mortality group had significantly higher door-to-balloon time (DTBT), Systemic Inflammatory Response Index (SIRI), pan-immune-inflammation value (PIV), whereas body mass index (BMI), Prognostic Nutritional Index (PNI), and Advanced Lung Cancer Inflammation Index (ALI) values were significantly lower (p < 0.001). Among the ML models, the XGBoost algorithm achieved the best performance, with 98.99% accuracy, a ROC-AUC of 0.999, and 100% sensitivity, correctly identifying all mortality cases. SHAP analysis identified DTBT, albumin level, and ALI score as the strongest predictors of mortality, in that order. Conclusions: The XGBoost algorithm provides high accuracy and reliability for predicting long-term mortality in STEMI patients. Beyond DTBT, integrating novel indices—especially ALI and TyG—into ML models may serve as a powerful clinical tool for early identification of high-risk patients and improved risk stratification.

Aim: This study investigated whether the CHA2DS2-VASc score is an independent predictor of high thrombus burden and mortality in patients presenting with acute coronary syndrome (ACS) and Coronavirus Ddisease (COVID-19).Materials and Methods: Patients with acute coronary syndrome (ACS) and COVID-19 (n = 76) were included in the study. They were categorized into low thrombus burden (LTB; grades 1–3) and high thrombus burden (HTB; grades 4 and 5) groups according to the final thrombus score. The CHA2DS2-VAScscores were then compared between the two groups.Results: Post-procedural HTB developed in 50 patients (65.7%). The neutrophil-to-lymphocyte ratio (6.00 ± 3.73 vs. 11.45 ± 10.6; P < 0.05), creatinine (0.84 ± 0.22 vs. 1.51 ± 0.92 mg/dL; P < 0.05), blood urea nitrogen (42.27 ± 12.6 vs. 62.27 ± 48.2 mg/dL; P < 0.05), potassium (4.06 ± 0.35 vs. 4.51 ± 0.49 mEq/L; P < 0.05), ferritin (286 ± 55.2 vs. 730 ± 96.8 ng/mL; P < 0.05), interleukin-6 (18.12 ± 7.14 vs. 186.66 ± 56.8 pg/mL; P < 0.05), lactate dehydrogenase (425.7 ± 31.2 vs. 1002.7 ± 173.4 U/L; P < 0.05), and CHA2DS2-VASc score (2.84 ± 1.27 vs. 4.08 ± 1.61; P < 0.05) were significantly higher in the HTB group. Mortality [3 (11.5%) vs 23 (46.0%), P<0.05)] and CHA2DS2-VASc score (2.84 ± 1.27 vs 4.08 ± 1.61, P<0.05) were higher in the HTB group (Table 1).Conclusions: In this study, the easily calculated CHA2DS2-VASc score was an independent predictor of HTB in patients with COVID-19 presenting with ACS. In addition, it predicted mortality in the same patient group.

Objectives: Warfarin resistance represents a rare yet clinically significant challenge, especially among patients with mechanical heart valves. It may result from either hereditary or acquired factors. Case presentation: A 27-year-old male patient with a history of aortic and mitral valve replacement was followed with subtherapeutic International Normalized Ratio (INR) of 1.8–2.0 despite receiving 20 mg/day of warfarin. He was hospitalized for evaluation, and potential acquired causes of warfarin resistance were excluded. The patient was discharged with a plan for close INR monitoring. Following the initiation of lorazepam and olanzapine for a comorbid psychiatric condition, he re-presented with bleeding manifestations due to warfarin overdose. Notably, his apparent warfarin resistance resolved after the addition of these medications, and he has since been maintained within the therapeutic INR range on a stable warfarin dose of 5 mg/day. Conclusions: Warfarin is known to interact with numerous medications, and new drug interactions continue to be reported in the literature. Although no major interactions with lorazepam or olanzapine have been previously documented, in this case the concomitant initiation of these agents appeared to overcome warfarin resistance. This clinical course was remarkable for the apparent resolution of warfarin resistance, raising the possibility of underlying pharmacologic interactions.

Hypertrophic cardiomyopathy (HCM) is a genetic cardiac disease associated with an increased risk of sudden cardiac death. Left ventricular (LV) apical aneurysms may develop in patients with HCM and are linked to an adverse prognosis. We present the case of a 68-year-old woman with HCM who was found to have aneurysmal dilatation of the LV basal segments on transthoracic echocardiography. Coronary angiography revealed no obstructive epicardial coronary artery disease. Unlike the typical apical aneurysm pattern, this case highlights a basal segment aneurysm in HCM and underscores the importance of careful echocardiographic evaluation in the diagnosis and follow-up of these patients.