Browsing by Author "Uccelli, Matteo (55782599300)"

Introduction: There has been an increasing interest for the laparoscopic treatment of early gastric cancer, especially among Eastern surgeons. However, the oncological effectiveness of Laparoscopic Gastrectomy (LG) for Advanced Gastric Cancer (AGC) remains a subject of debate, especially in Western countries where limited reports have been published. The aim of this paper is to retrospectively analyze short- and long-term results of LG for AGC in a real-life Western practice. Materials and methods: All consecutive cases of LG with D2 lymphadenectomy for AGC performed from January 2005 to December 2019 at seven different surgical departments were analyzed retrospectively. The primary outcome was diseases-free survival (DFS). Secondary outcomes were overall survival (OS), number of retrieved lymph nodes, postoperative morbidity and conversion rate. Results: A total of 366 patients with stage II and III AGC underwent either total or subtotal LG. The mean number of harvested lymph nodes was 25 ± 14. The mean hospital stay was 13 ± 10 days and overall postoperative morbidity rate 27.32%, with severe complications (grade ≥ III) accounting for 9.29%. The median follow-up was 36 ± 16 months during which 90 deaths occurred, all due to disease progression. The DFS and OS probability was equal to 0.85 (95% CI 0.81–0.89) and 0.94 (95% CI 0.92–0.97) at 1 year, 0.62 (95% CI 0.55–0.69) and 0.63 (95% CI 0.56–0.71) at 5 years, respectively. Conclusion: Our study has led us to conclude that LG for AGC is feasible and safe in the general practice of Western institutions when performed by trained surgeons. © 2021, The Author(s).

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. © The Author(s) 2023.