Background: This study aimed to investigate the performance of two versions of ChatGPT (o1 and 4o) in making decisions about coronary revascularization and to compare the recommendations of these versions with those of a multidisciplinary Heart Team. Moreover, the study aimed to assess whether the decisions generated by ChatGPT, based on the internal knowledge base of the system and clinical guidelines, align with expert recommendations in real-world coronary artery disease management. Given the increasing prevalence and processing capabilities of large language models, such as ChatGPT, this comparison offers insights into the potential applicability of these systems in complex clinical decision-making. Methods: We conducted a retrospective study at a single center, which included 128 patients who underwent coronary angiography between August and September 2024. The demographics, medical history, current medications, echocardiographic findings, and angiographic findings for each patient were provided to the two ChatGPT versions. The two models were then asked to choose one of three treatment options: coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), or medical therapy, and to justify their choice. Performance was assessed using metrics such as accuracy, sensitivity, specificity, precision, F1 score, Cohen's kappa, and Shannon's entropy. Results: The Heart Team recommended CABG for 78.1% of the patients, PCI for 12.5%, and medical therapy for 9.4%. ChatGPT o1 demonstrated higher sensitivity in identifying patients who needed CABG (82%) but lower sensitivity for PCI (43.7%), whereas ChatGPT 4o performed better in recognizing PCI candidates (68.7%) but was less accurate for CABG cases (43%). Both models struggled to identify patients suitable for medical therapy, with no correct predictions in this category. Agreement with the Heart Team was low (Cohen's kappa: 0.17 for o1 and 0.03 for 4o). Notably, these errors were often attributed to the limited understanding of the model in a clinical context and the inability to analyze angiographic images directly. Conclusion: While ChatGPT-based artificial intelligence (AI) models show promise in assisting with cardiac care decisions, the current limitations of these models emphasize the need for further development. Incorporating imaging data and enhancing comprehension of clinical context is essential to improve the reliability of these AI models in real-world medical settings.

Aim: Patient awareness and disease-specific knowledge are essential for shared decision-making of patients with abdominal aortic aneurysms. With this pilot survey, we aimed to figure out the obstacles to patient's awareness about the aortic aneurysm before and after the procedure. Material and Methods: Patients who experienced elective endovascular aortic aneurysm repair (EVAR) in our Cardiovascular Surgery Clinic between 2019 to 2023 were the selected patient cohort. The first 50 patients who visited our outpatient clinic were given a questionnaire about their awareness of the aneurysm disease, disease-specific knowledge, and the comprehensibility of the patient information provided before and after the procedure.Results: The mean age of our patients was 66±6.9. Younger patients were more aware of the situation before the information (p=0.013). Patients anxious about the disease were also more conscious about the aortic aneurysm (p=0.02). Although all patients were given preoperative information and disease-specific information by the same team, 13 patients (26%) could not recall anything about the disease and did not recall what operation was performed and why. Thirty-seven patients (74%) gained awareness about the disease. The patients with at least an educational level above high school gained more awareness than others (p=0.04). Conclusion: The Classical informatory model seems insufficient for gaining awareness and consciousness for older patients and with patients with low level of education. Strengthened patient-practitioner interaction with supplemental technologies (leaflets, interactive media, audio tapes, etc.) may improve these patients' shared decision-making. More prospective research is required in this regard.

Aim: End-stage renal disease (ESRD) presents significant challenges for patients and healthcare systems. Treatment options include renal transplant, peritoneal dialysis, and hemodialysis, with hemodialysis being the most common, necessitating suitable vascular access like arteriovenous fistula (AVF), graft, or catheter. This study aims to analyze the quality of YouTube videos on vascular access for hemodialysis, using the 2018 Clinical Practice Guidelines of the European Society for Vascular Surgery (ESVS) as a benchmark and employing JAMA, Global Quality, and DISCERN scores. To our knowledge, this is the first study evaluating YouTube content quality on this topic.Material and Methods: A YouTube search for 'arteriovenous fistula' was conducted, analyzing the first 200 videos based on predetermined criteria. Exclusions included videos lacking sound, not in English, off-topic, or duplicates. Data collected included uploader details, upload date, views, comments, likes, and duration. Video accuracy was assessed using the DISCERN tool, JAMA Benchmark Criteria, and Global Quality Scoring System (GQSS).Results: Out of 200 videos, 13 were excluded, leaving 187 for analysis. The interobserver agreement was high (κ=0.967). The videos amassed 12,854,643 views, with a median duration of 5 minutes and a median of 3412 views per video. Most views were for videos with poor DISCERN scores. There was a significant association between DISCERN scores and video characteristics. Videos with higher DISCERN scores had longer durations (p=0.01). However, videos with lower scores received more likes and views (p<0.01). The mean DISCERN score was 33.7, indicating poor quality, with only 18.8% rated as good or excellent.Conclusion: The study underscores the variability in the quality of YouTube content regarding vascular access for hemodialysis. Patients are encouraged to prioritize videos uploaded by healthcare professionals, ensuring both quality and accuracy. Despite limitations, this study contributes to informed decision-making in the context of hemodialysis vascular access.

Background: This study aims to investigate the effects of deep parasternal intercostal plane block on left internal thoracic artery vasospasm in coronary artery bypass grafting patients. Methods: Between March 2024 and August 2024, a total of 29 patients (24 males, 5 females; mean age: 60.1±8.3 years; range, 56 to 66 years) who were scheduled for elective coronary artery bypass grafting were included in this prospective study. An ultrasound-guided bilateral deep parasternal intercostal plane block was performed with 15 mL of 0.25% bupivacaine per side after anesthesia induction. Left internal thoracic artery peak systolic velocity, end-diastolic velocity, and resistive index, along with heart rate and mean arterial pressure, were recorded immediately before the block (T0) and 30 min after (T1). Demographics, body mass index, and comorbidities of the patients were noted. Results: After deep parasternal intercostal plane block administration, the left internal thoracic artery resistivity index decreased significantly (p=0.041), and the left internal thoracic artery diameter increased significantly (p=0.004). Although the peak systolic velocity increased and the end-diastolic velocity decreased following the block, these changes were not statistically significant (p=0.145 and p=0.135, respectively). Conclusion: Our study findings suggest that deep parasternal intercostal plane block administration may prevent left internal thoracic artery vasospasm by increasing arterial conduit diameter and reducing the resistivity index. Based on these findings, we believe that this method can be safely applied under ultrasound guidance without complications.