Surgeries, Volume 6, Issue 1 (March 2025) – 9 articles

Regional anesthesia has gained increasing attention in pediatric surgery as a valuable tool for managing perioperative pain and improving surgical outcomes. This narrative review highlights the numerous advantages of regional anesthesia in pediatric populations, including superior pain control, reduced reliance on systemic opioids, fewer anesthetic-related complications, and enhanced recovery profiles. Using ultrasound-guided techniques has further expanded the safety and precision of regional blocks in children. Regional anesthesia also addresses critical concerns about the potential neurotoxicity of general anesthetics in developing brains, offering a safer alternative or complement for specific procedures. Reducing systemic anesthetic and opioid exposure minimizes the risk of adverse effects such as respiratory depression, nausea, and sedation, which are particularly significant in medically fragile or younger patients. Furthermore, regional techniques contribute to faster recovery times, better preservation of neurophysiological monitoring signals during surgery, and attenuation of the stress response. The integration of adjuvants like clonidine, dexmedetomidine, and dexamethasone further enhances the efficacy and duration of regional blocks while improving safety profiles. Despite these benefits, implementing regional anesthesia in pediatric populations requires specialized expertise and an understanding of children’s unique anatomical and physiological differences. This review underscores the growing role of regional anesthesia in modern pediatric perioperative care. It highlights its potential to optimize outcomes, reduce complications, and address emerging concerns about the safety of general anesthesia in children undergoing surgery. Full article

Background: Lung cancer surgery often involves complex decision-making, where accurate and interpretable predictive models are crucial for assessing postoperative risks and optimizing outcomes. This study presents XplainLungSHAP, a novel framework combining SHAP (SHapley Additive exPlanations) and attention mechanisms to enhance both predictive accuracy and transparency. The aim is to support clinicians in preoperative evaluations by identifying and prioritizing key clinical features. Methods: The framework was developed using data from 470 patients undergoing lung cancer surgery. Key clinical features were identified through SHAP, ensuring alignment with medical expertise. These features were dynamically weighted using an attention mechanism in a neural network, enhancing their impact on survival predictions. The model’s performance was evaluated through accuracy, confusion matrices, and ROC analysis, demonstrating its reliability and interpretability. Results: The XplainLungSHAP model achieved an accuracy of 91.49%, outperforming traditional machine learning models. SHAP analysis identified critical predictors, including pulmonary function, comorbidities, and age, while the attention mechanism prioritized these features dynamically. The combined approach ensured high accuracy and offered actionable insights into survival predictions. Conclusions: XplainLungSHAP addresses the limitations of black-box models by integrating explainability with state-of-the-art predictive techniques. This framework provides a transparent and clinically relevant tool for guiding surgical decisions, supporting personalized care, and advancing AI applications in thoracic oncology. Full article

Background/Objectives: Among the scientific literature, the significant potential of the application of artificial intelligence (AI) in minimally invasive surgery (MIS) stands out. The aim of this study is to provide a comprehensive review to analyze the scientific literature on AI applications in MIS training, selecting the main applications, limitations, opportunities and challenges in this field of research. Methods/Design: A literature search was conducted in scientific databases. The search was performed with titles or abstracts, using keywords. First, studies unrelated to the topic of study were eliminated. Next, the selection was limited to articles in English. The exclusion criteria for the search were reviews, letters, case reports, industrial articles and conference abstracts. Next, only studies published in the last ten years (2014–2024) were evaluated, with priority given to publications in the last five years (2019–2024) in surgical training in AI and MIS. Finally, the full text was reviewed to add or exclude the study from this review. Results: Of the 54 studies included in this review, 18 studies were related to skills assessment, 30 studies analyzed aspects of surgical training itself, 12 studies were related to learning aspects of surgical planning, 7 studies were based on gesture recognition and 3 studies were based on surgical action recognition to measure surgical performance during MIS training. A brief description of the main AI techniques was included in this review. Conclusions: The application of AI in MIS surgical training is still a developing field of research, which presents great potential for exploring future applications, challenges, opportunities and drawbacks, as well as synergies between the technical and clinical research fields. Full article

It was in 1989 that we first reported on the use of the radial artery (RA) as a secondary arterial graft for coronary artery bypass grafting (CABG). Nevertheless, discrepancies in clinical endpoints between the RA and alternative conduits have been reported in consecutive randomised trials. With over fifty years of accumulated practice in RA bypass grafting, we sought to identify the second-best option for CABG by reviewing the literature. A consistently successful second-best conduit for CABG has been demonstrated using the radial artery. Compared to saphenous vein grafts, the findings indicate improved outcomes and better patency results. Furthermore, it has been demonstrated to be a safe and effective conduit in the territory of the right coronary artery. The lack of available literature and the scarcity of similar case series restrict the application of the gastroepiploic artery. After five decades of utilisation, it can be unequivocally stated that the radial artery is the optimal conduit for coronary bypass surgery following the left internal thoracic artery to the left anterior descending artery. Full article

Background/Objectives: Pressure injuries (PIs) are injuries to the skin and underlying tissue localized over a bony prominence. Surgical complications following the closure of a PI include ulcer recurrence, wound dehiscence, hematomas, and infection, which pose significant morbidity issues to patients. The objective of this study is to characterize the relationship between BMI and early and late wound outcomes following surgical closure through a secondary analysis of a previous study examining the effect of two support surfaces on PI healing. Methods: A single institution study on patients with a stage 3/4 pressure injury admitted for surgical closure was conducted. The subjects were monitored for 14 days post-closure (POD-14) so that an assessment of their early wound status and complications, including moisture, maceration, drainage, dehiscence, epidermolysis, necrosis, and demarcation, could be conducted. Results: In total, 68 patients were included. Out of these, 13% of patients were underweight, 29% were normal-weight, 35% were overweight, and 22% were obese. POD-14 complications occurred in 22% of underweight patients, 15% of normal-weight patients, 38% of overweight patients, and 40% of obese patients. Of all recorded complications, 75% of patients were overweight or obese. Complication rates were not significantly different based on osteomyelitis status. The most common cultures identified in wounds were P. aeruginosa, S. aureus, and E. coli. Negative cultures were found in 22% of closed wounds and 13% of open wounds. Conclusions: Our findings suggest that BMIs may be correlated with early wound status and the incidence of postoperative complications, while it may not be correlated with osteomyelitis status. Future studies should further evaluate the effect of BMIs on pressure injury-associated complications. This may further guide preoperative planning and patient expectations. Full article

Aortic stenosis (AS) is the most common valve disease in developed countries, with severe cases traditionally managed through surgical aortic valve replacement (SAVR). More recently, transcatheter aortic valve replacement (TAVR) has been used as a less invasive alternative, especially for patients deemed high-risk for surgery. This review aims to compare SAVR and TAVR by examining the efficacy, patient selection criteria, complications, and evolving guidelines. SAVR is the preferred option for patients at low surgical risk or with anatomical challenges unsuitable for TAVR. It offers well-documented durability and favorable long-term survival. Conversely, TAVR has gained acceptance for intermediate- and high-risk patients, with shorter recovery times and reduced immediate postoperative risks. However, questions surrounding its long-term durability in younger populations persist. Complications differ between the approaches, with TAVR associated with vascular access injuries and arrhythmic events, while SAVR presents risks tied to open surgery. As clinical guidelines evolve, patient age, comorbidities, and life expectancy play critical roles in determining the optimal intervention. This review highlights the need for tailored treatment approaches, given the expanding indications and evolving evidence for both SAVR and TAVR in AS management. Full article

Background: This study evaluated the performance of machine learning models trained on two different datasets of knee X-ray images annotated with Kellgren–Lawrence grades. Methods: Learning curves indicated that one model experienced poor training, characterized by underfitting, while the other model demonstrated effective training with proper convergence. The poorly trained model appeared to perform adequately on its internal test set but failed to generalize to an external dataset, yielding suboptimal results. Results: In contrast, the well-trained model not only performed well on its internal validation but also showed adequate performance when tested on the external dataset. Conclusions: These findings highlight the importance of examining learning curves to assess model training quality and the critical necessity of external testing to evaluate generalizability. Most existing studies lack external validation, raising concerns about the reliability of their reported performance. This study emphasizes that without external testing, models may not perform as expected in real-world clinical settings, potentially impacting clinical decision-making for surgical interventions. The results advocate for the inclusion of external validation in model evaluation and the assessment of model convergence using learning curves to ensure the development of robust and generalizable tools for knee osteoarthritis severity assessment and other applications. Full article

Background: Diversity of gender representation in surgery is known to positively influence patient outcomes and predict career trajectories for female trainees. This study aims to identify the current and recent past state of gender diversity amongst trainees entering Canadian surgical residency programs. Methods: Data were sourced from the Canadian Post-M.D. Education Registry (CAPER) and the Canadian Resident Matching Service (CaRMs) for ten surgical specialties. CAPER data include PGY-1 trainees in all surgical specialties for the academic years 2012–2013 to 2021–2022. CaRMs provided data of total applicants and matched applicants for Canadian Medical Graduates (CMGs) in the match years 2013–2022. Results: From 2012–2022, there were 4011 PGY-1 surgical residents across Canada (50.4% female, 49.6% male). The surgical specialties with the most female representation were obstetrics/gynecology (82.1–91.9%), general surgery (40.2–70.7%), and plastic surgery (33.3–55.6%). The surgical specialties with the least female representation were neurosurgery (18.7–35.3%), urology (11.8–42%), and orthopedic surgery (17.5–38.5%). The number of female applicants to surgical programs has increased since 2013 and outnumbers male applicants each subsequent year. The match rate to surgical programs for female applicants has varied by year, with the highest being 63.9% in 2014 and the lowest in 2018 at 48.8%. Conclusions: Our study shows promising trends that reflect increased representation of female trainees. However, while the number of female trainees in general surgery and obstetrics/gynecology programs matches and even exceeds Canadian demographic proportions, this is not true for most other surgical specialties. This calls for continued efforts to improve and retain gender equity across surgical specialties in Canada. Full article

Background/Objectives: Myocardial revascularization surgery (MR) is routinely performed in hospitals. However, there is a lack of an algorithm in the scientific literature aimed at predicting intraoperative parameters, such as total surgery time (TST) and cardiopulmonary bypass time (CBT), based on preoperative MR parameters. Therefore, the objective of the present study is to apply a complex network model to predict parameters associated with TST and CBT. Methods: Retrospective data from 124 patients who underwent MR, including medical history, vital signs, and laboratory/biochemical tests, were used, with 30 patients contributing to the construction of the network. Three complex networks were created to study the targets (TST and CBT). The Eigenvector metric was employed to investigate the parameters most relevant to these targets. Results: Regardless of the target, parameters derived from the blood gas analysis followed by erythrogram displayed greater relevance according to the eigenvector metric. However, for TST, the most prominent parameter was Red Blood Cells, while, for CBT, Diastolic Blood Pressure emerged as the most important variable. Conclusion: The targeted complex network model revealed that pulmonary, hemodynamic, and perfusion factors are relevant to the intraoperative parameters of MR. The networks also demonstrated that, although the targets show significant correlation with each other (TST and CBT-r = 0.76; p = 0.000), the importance of the parameters in the networks does not follow the same order. This reiterates the strength of the network in revealing specific information when a particular target is selected. Full article