Journal of the American College of Surgeons
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Randomized Controlled Trial Multicenter Study
Predicting Futility in Severely Injured Patients: Using Arrival Lab Values and Physiology to Support Evidence-Based Resource Stewardship.
The recent pandemic exposed a largely unrecognized threat to medical resources, including daily available blood products. Some of the most severely injured patients who arrive in extremis consume tremendous resources yet succumb shortly after arrival. We sought to identify cut points available early in the patient's resuscitation that predicted 100% mortality. ⋯ The use of evidence-based STOP criteria provides cut points of futility to help guide early decisions for discontinuing aggressive treatment of severely injured patients arriving in extremis.
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We reviewed our management strategy and outcome data for all 311 patients less than 18 years of age who underwent 323 heart transplants at our institution (1986 to 2022) in order to assess changes in patterns of practice and outcomes over time and to compare two consecutive eras: era 1 (154 heart transplants [1986 to 2010]) and era 2 (169 heart transplants [2011 to 2022]). ⋯ Patients undergoing cardiac transplantation in the most recent era are higher risk but have better survival.
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Parathyroidectomy (PTx) is the most effective treatment for secondary hyperparathyroidism. Literature regarding the effect of surgical approaches on postoperative hypocalcemia is limited and mainly focuses on postoperative calcium levels. This study aims to evaluate the association of subtotal PTx and total PTx with autotransplantation for secondary hyperparathyroidism with postoperative hypocalcemia. ⋯ Subtotal parathyroidectomy is associated with less postoperative hypocalcemia and provides similar surgical cure for dialysis patients with secondary hyperparathyroidism.
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Elucidating contributors affecting liver transplant survival is paramount. Current methods offer crude global group outcomes. To refine patient-specific mortality probability estimation and to determine covariate interaction using recipient and donor data, we generated a survival tree algorithm, Recipient Survival After Orthotopic Liver Transplantation (ReSOLT), using United Network Organ Sharing (UNOS) transplant data. ⋯ Survival trees are a flexible and effective approach to understand the effects and interactions of covariates on survival. Individualized survival probability following liver transplant is possible with ReSOLT, allowing for more coherent patient and family counseling and prediction of patient outcome using both recipient and donor factors.