Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
-
The COVID-19 pandemic has placed acute care providers in demanding situations in predicting disease given the clinical variability, desire to cohort patients, and high variance in testing availability. An approach to stratifying patients by likelihood of disease based on rapidly available emergency department (ED) clinical data would offer significant operational and clinical value. The purpose of this study was to develop and internally validate a predictive model to aid in the discrimination of patients undergoing investigation for COVID-19. ⋯ The derived predictive models offer good discriminating capacity for COVID-19 disease and provide interpretable and usable methods for those providers caring for these patients at the important crossroads of the community and the health system. We found utilization of the logistic regression model utilizing exposure history, temperature, WBC, and chest X-ray result had the greatest discriminatory capacity with the most interpretable model. Integrating a predictive model-based approach to COVID-19 testing decisions and patient care pathways and locations could add efficiency and accuracy to decrease uncertainty.
-
Clinical guidelines have supported outpatient treatment of low-risk pulmonary embolism (PE) since 2014, but adoption of this practice has been slow. Direct oral anticoagulant (DOAC) therapy for venous thromboembolism (VTE) is now as common as vitamin K antagonist treatment, but data are sparse regarding outcomes for patients with low-risk PE treated with DOACs as outpatients. We conducted a systematic review of literature on outcomes of outpatient management for PE, including comparisons to inpatient treatment and differences by anticoagulant class. ⋯ Among patients with low-risk PE treated as outpatients, few patients experienced major adverse outcomes such as mortality, recurrent VTE, or major bleeding within 90 days.