Annals of surgery
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To evaluate the downstream effects of the COVID-19 generated surgical backlog. ⋯ An over 20% reduction in elective surgeries and an increase in urgent cholecystectomies was observed during the COVID-19 period suggesting a rebound effect secondary to the surgical backlog. The COVID-19 generated surgical backlog will have a heterogeneous downstream effect with significant implications for surgical recovery planning.
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To develop a deep learning model to automatically segment hepatocystic anatomy and assess the criteria defining the critical view of safety (CVS) in laparoscopic cholecystectomy (LC). ⋯ Deep learning algorithms can be trained to reliably segment hepatocystic anatomy and assess CVS criteria in still laparoscopic images. Surgical-technical partnerships should be encouraged to develop and evaluate deep learning models to improve surgical safety.
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We aimed to determine a safe zone of intraoperative fluid management associated with the lowest postoperative complication rates without increased acute kidney injury (AKi) risk for elective colorectal surgery patients. ⋯ Total intraoperative RL ≥2.7 L was independently associated with postoperative ileus and prolonged LOS in elective colorectal surgery patients. A new potential standard for intraoperative fluids will require anesthesia case planning (complexity and duration) to ensure total fluid volume meets this new opportunity to improve care.