Journal of the American College of Surgeons
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Healthcare is responsible for 8.5% of US greenhouse gas emissions. This impact must be mitigated while maintaining clinical excellence. This study compares clinical outcomes, cost-efficiency, and climate impact of transumbilical laparoscopic-assisted appendectomy (TULAA) vs 3-port laparoscopic appendectomy (LA). ⋯ Although patient safety and excellent clinical outcomes must remain the top priority in healthcare, the current environmental crisis demands consideration of climate impact. When clinical noninferiority can be demonstrated, treatment options with fewer greenhouse gas emissions should be chosen.
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Primary aldosteronism (PA) is the most common cause of secondary hypertension, yet screening remains startlingly infrequent. We describe (1) PA screening practices in a large, diverse health system, (2) the development of a computable phenotype for PA screening, and (3) the design and pilot deployment of an electronic health record (EHR)-based active choice nudge to recommend PA screening. ⋯ PA screening rates are low. This pilot study suggests an EHR-based nudge leveraging a precise computable phenotype can dramatically increase appropriate PA screening.
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Structured preparation is necessary to conduct quality improvement (QI) strategies that are relevant to the problem, feasible, appropriately resourced, and potentially effective. Recent work suggests that improvement efforts are suboptimally conducted. Our goal was to determine how well preparation for surgical QI is undertaken, including detailing the problem, setting project goals, and planning an intervention. ⋯ Thorough planning is a critical component of effective QI, and our study reflects significant opportunity for its improvement. The ACS Quality Framework may serve as a guide to improve QI planning, thereby promoting efficiency and effectiveness of these efforts.
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The success of parathyroidectomy in primary hyperparathyroidism depends on the intraoperative differentiation of diseased from normal glands. Deep learning can potentially be applied to digitalize this subjective interpretation process that relies heavily on surgeon expertise. In this study, we aimed to investigate whether diseased vs normal parathyroid glands have different near-infrared autofluorescence (NIRAF) signatures and whether related deep learning models can predict normal vs diseased parathyroid glands based on intraoperative in vivo images. ⋯ Normal and diseased parathyroid glands in primary hyperparathyroidism have different intraoperative NIRAF patterns that could be quantified with intensity and heterogeneity analyses. Visual deep learning models relying on these NIRAF signatures could be built to assist surgeons in differentiating normal from diseased parathyroid glands.