Anemia is seen frequently in critically ill patients and has several etiologies. This article reviews the causes with an emphasis on the effects of inflammation, examines the risks and benefits of current therapies, and discusses novel treatment options.
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Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA.
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Radbound Univeristy Medical Center, Nijmegen, Netherlands;
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View Article and Find Full Text PDFPredicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm - a 10-year multicenter retrospective study.
Front Med (Lausanne)
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Department of General Surgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China.
Background: Gastroparesis following complete mesocolic excision (CME) can precipitate a cascade of severe complications, which may significantly hinder postoperative recovery and diminish the patient's quality of life. In the present study, four advanced machine learning algorithms-Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), and -nearest neighbor (KNN)-were employed to develop predictive models. The clinical data of critically ill patients transferred to the intensive care unit (ICU) post-CME were meticulously analyzed to identify key risk factors associated with the development of gastroparesis.
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