Annals of surgery
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To investigate the long-term dynamics of recurrence risk and the significance of prognostic variables using conditional recurrence-free survival (C-RFS) analysis in neoadjuvant treatment (NAT) for resectable (R) and borderline resectable (BR) pancreatic cancer (PC). ⋯ In NAT for R/BRPC, the probability of gaining additional RFS increases as a function of RFS already accrued, and the significance of prognostic variables time-dependently evolves in their own patterns during the long-term postoperative period.
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Randomized Controlled Trial
Omics Signatures of Tissue Injury and Hemorrhagic Shock in Swine.
Advanced mass spectrometry methods were leveraged to analyze both proteomics and metabolomics signatures in plasma upon controlled tissue injury (TI) and hemorrhagic shock (HS)-isolated or combined-in a swine model, followed by correlation to viscoelastic measurements of coagulopathy via thrombelastography. ⋯ The current study provides a comprehensive characterization of proteomic and metabolomic alterations to combined or isolated TI and HS in a swine model and identifies early and late omics correlates to viscoelastic measurements in this system.
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To assess the feasibility, proficiency, and mastery learning curves for robotic pancreatoduodenectomy (RPD) in "second-generation" RPD centers following a multicenter training program adhering to the IDEAL framework. ⋯ The feasibility, proficiency, and mastery learning curves for RPD at 15, 62, and 84 procedures in "second-generation" centers after a multicenter training program were considerably shorter than previously reported from "pioneering" expert centers. The learning curve cutoffs and prior laparoscopic experience did not impact major morbidity and mortality. These findings demonstrate the safety and value of a nationwide training program for RPD in centers with sufficient volume.
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To assess whether the risk of persistent opioid use after surgery varies by payer type. ⋯ Persistent opioid use remains common among individuals undergoing surgery and higher among patients with Medicaid insurance. Strategies to optimize postoperative recovery should focus on adequate pain management for all patients and consider tailored pathways for those at risk.
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To implement a machine learning model using only the restricted data available at case creation time to predict surgical case length for multiple services at different locations. ⋯ We created a unique framework that is being leveraged every day to predict surgical case length more accurately at case posting time and could be potentially utilized to deploy future machine learning models.