Journal of pediatric surgery
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The rapid spread of coronavirus disease 2019 (COVID-19) has exceeded the standard capacity of many hospital systems and led to an unprecedented scarcity of resources, including the already limited resource of extracorporeal membrane oxygenation (ECMO). With the large amount of critically ill patients and the highly contagious nature of the virus, significant consideration of ECMO candidacy is crucial for both appropriate allocation of resources as well as ensuring protection of health care personnel. ⋯ This article describes our changes in consultation, cannulation, and daily care of COVID-19 positive patients requiring ECMO as well as discusses strategies for ensuring safety of our ECMO healthcare personnel and optimal allocation of resources. LEVEL OF EVIDENCE: Level V.
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During the COVID-19 pandemic, experience-based guidelines are needed in the pediatric population in order to deliver high quality care in a new way that keeps patients and healthcare workers safe and maximizes hospital resource utilization. ⋯ Clinical research paper LEVEL OF EVIDENCE: Level V.
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Surgery for pectus excavatum is associated with significant postoperative pain. The aim of this study was to summarize the current literature regarding postoperative pain control for pediatric patients undergoing minimally invasive repair of pectus excavatum (MIRPE). ⋯ 2A [1].
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Randomized controlled trials (RCT) in pediatric appendicitis remain limited, and the robustness of available evidence is unknown. The aim of this study was to determine the fragility of results in pediatric appendicitis RCTs. ⋯ Level I.
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Exponential growth in computing power, data storage, and sensing technology has led to a world in which we can both capture and analyze incredible amounts of data. The evolution of machine learning has further advanced the ability of computers to develop insights from massive data sets that are beyond the capacity of human analysis. The convergence of computational power, data storage, connectivity, and Artificial Intelligence (AI) has led to health technologies that, to date, have focused on diagnostic areas such as radiology and pathology. ⋯ There are three main areas where the authors believe that AI could impact surgery in the near future: enhancement of training modalities, cognitive enhancement of the surgeon, and procedural automation. While the promise of Big Data, AI, and Automation is high, there have been unanticipated missteps in the use of such technologies that are worth considering as we evaluate how such technologies could/should be adopted in surgical practice. Surgeons must be prepared to adopt smarter training modalities, supervise the learning of machines that can enhance cognitive function, and ultimately oversee autonomous surgery without allowing for a decay in the surgeon's operating skills.