Annals of emergency medicine
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Multicenter Study
Use of Machine Learning to Develop a Risk-Stratification Tool for Emergency Department Patients With Acute Heart Failure.
We use variables from a recently derived acute heart failure risk-stratification rule (STRATIFY) as a basis to develop and optimize risk prediction using additional patient clinical data from electronic health records and machine-learning models. ⋯ Use of a machine-learning model with additional variables improved 30-day risk prediction compared with conventional approaches.
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Although induced abortion is generally a safe outpatient procedure, many patients subsequently present to the emergency department, concerned about a postabortion complication. It is helpful for emergency physicians to understand the medications and procedures used in abortion care in the United States to effectively and efficiently triage and treat women presenting with potential complications from an abortion. ⋯ This review also offers a comprehensive overview of management of abortion complications, including algorithms for more common complications and descriptions of less common but more severe adverse events. The article concludes with a recognition of the social stigma and legal regulations unique to abortion care.