Simulation in thoracic surgery—A mini review of a vital educational tool to maximize peri-operative care and minimize complications

Thoracic surgery is an increasingly expanding field, and the addition of national screening programs has resulted in increasing operative numbers and complexity. Thoracic surgery overall has an approximately 2% mortality and 20% morbidity with common specific complications including persistent air leak, pneumothorax, and fistulas. The nature of the surgery results in complications being unique to thoracic surgery and often very junior members of the surgical team feel underprepared to deal with these complications after very little exposure during their medical school and general surgical rotations. Throughout medicine, simulation is being increasingly used as a method to teach the management of complicated, rare, or significant risk occurrences and has shown significant benefits in learner confidence and outcomes. In this mini review we explain the learning theory and benefits of simulation learning. We also discuss the current state of simulation in thoracic surgery and its potential future in aiding complication management and patient safety

Surgeons' perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey

Background: Artificial intelligence (AI) is gaining traction in medicine and surgery. AI-based applications can offer tools to examine high-volume data to inform predictive analytics that supports complex decision-making processes. Time-sensitive trauma and emergency contexts are often challenging. The study aims to investigate trauma and emergency surgeons' knowledge and perception of using AI-based tools in clinical decision-making processes. Methods: An online survey grounded on literature regarding AI-enabled surgical decision-making aids was created by a multidisciplinary committee and endorsed by the World Society of Emergency Surgery (WSES). The survey was advertised to 917 WSES members through the society's website and Twitter profile. Results: 650 surgeons from 71 countries in five continents participated in the survey. Results depict the presence of technology enthusiasts and skeptics and surgeons' preference toward more classical decision-making aids like clinical guidelines, traditional training, and the support of their multidisciplinary colleagues. A lack of knowledge about several AI-related aspects emerges and is associated with mistrust. Discussion: The trauma and emergency surgical community is divided into those who firmly believe in the potential of AI and those who do not understand or trust AI-enabled surgical decision-making aids. Academic societies and surgical training programs should promote a foundational, working knowledge of clinical AI