Machine Learning-Based Risk Prediction of Critical Care Unit Admission for Advanced Stage High Grade Serous Ovarian Cancer Patients Undergoing Cytoreductive Surgery: The Leeds-Natal Score

Achieving complete surgical cytoreduction in advanced stage high grade serous ovarian cancer (HGSOC) patients warrants an availability of Critical Care Unit (CCU) beds. Machine Learning (ML) could be helpful in monitoring CCU admissions to improve standards of care. We aimed to improve the accuracy of predicting CCU admission in HGSOC patients by ML algorithms and developed an ML-based predictive score. A cohort of 291 advanced stage HGSOC patients with fully curated data was selected. Several linear and non-linear distances, and quadratic discriminant ML methods, were employed to derive prediction information for CCU admission. When all the variables were included in the model, the prediction accuracies were higher for linear discriminant (0.90) and quadratic discriminant (0.93) methods compared with conventional logistic regression (0.84). Feature selection identified pre-treatment albumin, surgical complexity score, estimated blood loss, operative time, and bowel resection with stoma as the most significant prediction features. The real-time prediction accuracy of the Graphical User Interface CCU calculator reached 95%. Limited, potentially modifiable, mostly intra-operative factors contributing to CCU admission were identified and suggest areas for targeted interventions. The accurate quantification of CCU admission patterns is critical information when counseling patients about peri-operative risks related to their cytoreductive surgery

BJS commission on surgery and perioperative care post-COVID-19

Background: Coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO on 11 March 2020 and global surgical practice was compromised. This Commission aimed to document and reflect on the changes seen in the surgical environment during the pandemic, by reviewing colleagues experiences and published evidence. Methods: In late 2020, BJS contacted colleagues across the global surgical community and asked them to describe how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had affected their practice. In addition to this, the Commission undertook a literature review on the impact of COVID-19 on surgery and perioperative care. A thematic analysis was performed to identify the issues most frequently encountered by the correspondents, as well as the solutions and ideas suggested to address them. Results: BJS received communications for this Commission from leading clinicians and academics across a variety of surgical specialties in every inhabited continent. The responses from all over the world provided insights into multiple facets of surgical practice from a governmental level to individual clinical practice and training. Conclusion: The COVID-19 pandemic has uncovered a variety of problems in healthcare systems, including negative impacts on surgical practice. Global surgical multidisciplinary teams are working collaboratively to address research questions about the future of surgery in the post-COVID-19 era. The COVID-19 pandemic is severely damaging surgical training. The establishment of a multidisciplinary ethics committee should be encouraged at all surgical oncology centres. Innovative leadership and collaboration is vital in the post-COVID-19 era

BJS commission on surgery and perioperative care post-COVID-19

Coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO on 11 March 2020 and global surgical practice was compromised. This Commission aimed to document and reflect on the changes seen in the surgical environment during the pandemic, by reviewing colleagues' experiences and published evidence