(1) Background: In the last few years, technological developments in the surgical field have been rapid and are continuously evolving. One of the most revolutionizing breakthroughs was the introduction of the IoT concept within surgical practice. Our systematic review aims to summarize the most important studies evaluating the IoT concept within surgical practice, focusing on Telesurgery and surgical Telementoring. (2) Methods: We conducted a systematic review of the current literature, focusing on the Internet of Surgical Things in Telesurgery and Telementoring. Forty-eight (48) studies were included in this review. As secondary research questions, we also included brief overviews of the use of IoT in image-guided surgery, and patient Telemonitoring, by systematically analyzing fourteen (14) and nineteen (19) studies, respectively. (3) Results: Data from 219 patients and 757 healthcare professionals were quantitively analyzed. Study designs were primarily observational or based on model development. Palpable advantages from the IoT incorporation mainly include less surgical hours, accessibility to high quality treatment, and safer and more effective surgical education. Despite the described technological advances, and proposed benefits of the systems presented, there are still identifiable gaps in the literature that need to be further explored in a systematic manner. (4) Conclusions: The use of the IoT concept within the surgery domain is a widely incorporated but less investigated concept. Advantages have become palpable over the past decade, yet further research is warranted.

Introduction Postoperative sepsis represents a significant problem in colorectal surgery patients. Aim: To identify the etiology as well as the risk factors associated with the development of postoperative sepsis, based on prospective data of patients undergoing colorectal surgery at...

Colon cancer is a major public health issue, affecting a growing number of individuals worldwide. Proper and early diagnosis of colon cancer is the necessary first step toward effective treatment and/or prevention of future disease relapse. Artificial intelligence and its subtypes, deep learning...

Introduction Sleeve gastrectomy (SG) is associated with short-term nutritional deficiencies postoperatively. This study evaluates the long-term percentage of excess weight loss (% EWL), and nutritional deficiencies in a single-centre cohort undergoing SG as a primary procedure, with a 6-year...

Aim To identify risk factors for developing surgical site infections (SSIs) based on a prospective study of patients undergoing colorectal surgery.Methods Between November 2019 and January 2021, 133 patients underwent elective operation for colorectal cancer in our institution. The following variables were recorded for each patient: age, gender, body mass index (BMI), American Society of Anesthesiologists Classification (ASA class), duration of surgery, wound classification, skin preparation regimens, surgical approach, comorbidities (hypertension, diabetes, cardiovascular disease, respiratory disease, chronic steroid use), and pathogens responsible for surgical site infection. Univariate analysis was performed using χ2 tests for categorical variables.Results A total of 65 males and 68 females were enrolled. Postoperative SSI was diagnosed in 29 (21.8%) cases. Fifty five patients were >70 years old, and SSIs were significantly more frequent in this group (p=0.033). There were 92 patients with BMI <30kg/m2 and 87 with ASA class ≤2; SSIs occurred significantly less frequently in these patients (p=0.021 and p=0.028, respectively). Open surgery was performed in 113 patients; 35 (out of 113; 31%) wound infections were classified as contaminated or dirty, and SSI occurred more often in these two groups (p=0.048 and p=0.037, respectively). Nineteen patients had diabetes and 36 used steroids continuously; SSI was significantly more frequent in these patients(p=0.021 and p=0.049, respectively).Conclusion Following colorectal cancer procedures SSIs were significantly more common among patients over 70 years old,BMI≥30kg/m2, ASA score>2, with diabetes and chronic steroid use, undergoing open, dirty or contaminated surgery. Escherichia coli and Enterococcus spp. were the two most common pathogens isolated.

Background: Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with its integration into cardiac surgery offering significant advancements in precision, efficiency, and patient outcomes. However, a comprehensive understanding of AI’s applications, benefits, challenges, and future directions in cardiac surgery is needed to inform its safe and effective implementation. Methods: A systematic review was conducted following PRISMA guidelines. Literature searches were performed in PubMed, Scopus, Cochrane Library, Google Scholar, and Web of Science, covering publications from January 2000 to November 2024. Studies focusing on AI applications in cardiac surgery, including risk stratification, surgical planning, intraoperative guidance, and postoperative management, were included. Data extraction and quality assessment were conducted using standardized tools, and findings were synthesized narratively. Results: A total of 121 studies were included in this review. AI demonstrated superior predictive capabilities in risk stratification, with machine learning models outperforming traditional scoring systems in mortality and complication prediction. Robotic-assisted systems enhanced surgical precision and minimized trauma, while computer vision and augmented cognition improved intraoperative guidance. Postoperative AI applications showed potential in predicting complications, supporting patient monitoring, and reducing healthcare costs. However, challenges such as data quality, validation, ethical considerations, and integration into clinical workflows remain significant barriers to widespread adoption. Conclusions: AI has the potential to revolutionize cardiac surgery by enhancing decision making, surgical accuracy, and patient outcomes. Addressing limitations related to data quality, bias, validation, and regulatory frameworks is essential for its safe and effective implementation. Future research should focus on interdisciplinary collaboration, robust testing, and the development of ethical and transparent AI systems to ensure equitable and sustainable advancements in cardiac surgery.