ABSTRACT
Hypoattenuated leaflet thickening (HALT), a potential aftereffect of transcatheter aortic valve replacement (TAVR) procedure, may affect valve performance and clinical outcomes. At this moment we describe an elderly patient who, despite being on prophylactic antiplatelet medication for previous percutaneous intervention (PCI) for coronary artery disease (CAD) and a self-expanding valve in-situ for aortic stenosis (TAVR), presented to the emergency room with non-ST-segment elevation myocardial infarction (NSTEMI), probably as a result of a thromboembolic event from HALT. The case highlights the significance of considering HALT-associated thromboembolism as a potential cause of myocardial infarction (MI) in post-TAVR patients.
ABSTRACT
Introduction Rapid advancements are being made in the field of Artificial Intelligence (AI) to support digital healthcare transformation and provide evidence-based care. The aim of this cross-sectional study was to evaluate the knowledge of basic principles, limitations, and applications of AI in healthcare among medical students and doctors of a developing country. Methods Two free webinars were hosted for doctors and medical students in northern India (Punjab state) to create awareness about the role of AI in healthcare and the recent advancements made in various medical specialties. The delegates' perceptions about their knowledge and interest in AI were ascertained using the Likert scale (1 = low, 5 = high) in the post-event questionnaire. Using Chi-square and cross-tabulation analysis, associations were examined between knowledge of AI, gender, medical experience, and other variables. Results Out of the total of 621 registrants, 367 filled the post-event questionnaire and were included in the analysis. Although the majority felt that AI will play an important role in delivering healthcare services in the future (74.4%), they did not feel knowledgeable about the applications (79.6%) and limitations of AI (82.8%). A relatively lesser proportion of doctors (51.6%) felt interested to learn more about AI than medical students (69.3%). Furthermore, a lesser proportion of doctors (65.2%) felt that AI will be beneficial for their career as a doctor as compared with medical students (84.4%). The majority of medical students (83.5%) had never attended any webinar/lecture or course on AI in healthcare and felt that they have received minimal advice (80.7%) from their medical school on teaching about AI and its applications. A significantly (P = 0.001) higher proportion of female medical students were unknowledgeable about the principles and applications of AI than male respondents. However, female medical students were significantly (P = 0.004) more interested than male medical students to learn about AI. Conclusions Formal training courses to teach about AI should be focused on to facilitate coherent and scientifically supported dissemination of knowledge in medical schools and hospitals. Further large-scale studies are needed to understand the perception and attitude of medical students and doctors regarding AI to steer policy development and medical education curriculum changes to spark an interest in emerging technologies and drive innovation.
