Journal of the American College of Surgeons
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Observational Study
Prospective Evaluation of Delirium in Geriatric Patients Undergoing Emergency General Surgery.
The prevalence of delirium and its impact on outcomes after emergency general surgery (EGS) remain unexplored. The aims of our study were to assess the impact of frailty on delirium and the impact of delirium on outcomes in geriatric EGS patients. ⋯ The incidence of delirium after EGS was 26%. Frailty and polypharmacy were associated with increased risk of delirium. Delirium appears to be associated with higher rates of in-hospital adverse events.
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Intraoperative drain use for pancreaticoduodenectomy has been practiced in an unconditional, binary manner (placement/no placement). Alternatively, dynamic drain management has been introduced, incorporating the Fistula Risk Score (FRS) and drain fluid amylase (DFA) analysis, to mitigate clinically relevant postoperative pancreatic fistula (CR-POPF). ⋯ This extended experience validates a dynamic drain management protocol, providing a model for better drain management and individualized patient care after pancreaticoduodenectomy. This study confirms that drains can be safely omitted from negligible/low-risk patients, and moderate/high-risk patients benefit from early drain removal.
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The common use of laparoscopic intervention produces impressive amounts of video data that are difficult to review for surgeons wishing to evaluate and improve their skills. Therefore, a need exists for the development of computer-based analysis of laparoscopic video to accelerate surgical training and assessment. We developed a surgical instrument detection system for video recordings of laparoscopic gastrectomy procedures. This system, the use of which might increase the efficiency of the video reviewing process, is based on the open source neural network platform, YOLOv3. ⋯ A new automated system to detect manipulation of surgical instruments in video recordings of laparoscopic gastrectomies based on the open source neural network platform, YOLOv3, was developed and validated successfully.