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Introduction: Prediction models for identifying emergency department (ED) patients at high risk of poor outcome are often not externally validated. We aimed to perform a head-to-head comparison of the discriminatory performance of several prediction models in a large cohort of ED patients., Methods: In this retrospective study, we selected prediction models that aim to predict poor outcome and we included adult medical ED patients. Primary outcome was 31-day mortality, secondary outcomes were 1-day mortality, 7-day mortality, and a composite endpoint of 31-day mortality and admission to intensive care unit (ICU).The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC). Finally, the prediction models with the highest performance to predict 31-day mortality were selected to further examine calibration and appropriate clinical cut-off points., Results: We included 19 prediction models and applied these to 2185 ED patients. Thirty-one-day mortality was 10.6% (231 patients), 1-day mortality was 1.4%, 7-day mortality was 4.4%, and 331 patients (15.1%) met the composite endpoint. The RISE UP and COPE score showed similar and very good discriminatory performance for 31-day mortality (AUC 0.86), 1-day mortality (AUC 0.87), 7-day mortality (AUC 0.86) and for the composite endpoint (AUC 0.81). Both scores were well calibrated. Almost no patients with RISE UP and COPE scores below 5% had an adverse outcome, while those with scores above 20% were at high risk of adverse outcome. Some of the other prediction models (i.e. APACHE II, NEWS, WPSS, MEWS, EWS and SOFA) showed significantly higher discriminatory performance for 1-day and 7-day mortality than for 31-day mortality., Conclusions: Head-to-head validation of 19 prediction models in medical ED patients showed that the RISE UP and COPE score outperformed other models regarding 31-day mortality.

Background: There is growing awareness that sex differences are associated with different patient outcomes in a variety of diseases. Studies investigating the effect of patient sex on sepsis-related mortality remain inconclusive and mainly focus on patients with severe sepsis and septic shock in the intensive care unit. We therefore investigated the association between patient sex and both clinical presentation and 30-day mortality in patients with the whole spectrum of sepsis severity presenting to the emergency department (ED) who were admitted to the hospital., Materials and Methods: In our multi-centre cohort study, we retrospectively investigated adult medical patients with sepsis in the ED. Multivariable analysis was used to evaluate the association between patient sex and all-cause 30-day mortality., Results: Of 2065 patients included, 47.6% were female. Female patients had significantly less comorbidities, lower Sequential Organ Failure Assessment score and abbreviated Mortality Emergency Department Sepsis score, and presented less frequently with thrombocytopenia and fever, compared to males. For both sexes, respiratory tract infections were predominant while female patients more often had urinary tract infections. Females showed lower 30-day mortality (10.1% vs. 13.6%; p  = .016), and in-hospital mortality (8.0% vs. 11.1%; p  = .02) compared to males. However, a multivariable logistic regression model showed that patient sex was not an independent predictor of 30-day mortality (OR 0.90; 95% CI 0.67-1.22; p  = .51)., Conclusions: Females with sepsis presenting to the ED had fewer comorbidities, lower disease severity, less often thrombocytopenia and fever and were more likely to have a urinary tract infection. Females had a lower in-hospital and 30-day mortality compared to males, but sex was not an independent predictor of 30-day mortality. The lower mortality in female patients may be explained by differences in comorbidity and clinical presentation compared to male patients.KEY MESSAGESOnly limited data exist on sex differences in sepsis patients presenting to the emergency department with the whole spectrum of sepsis severity.Female sepsis patients had a lower incidence of comorbidities, less disease severity and a different source of infection, which explains the lower 30-day mortality we found in female patients compared to male patients.We found that sex was not an independent predictor of 30-day mortality; however, the study was probably underpowered to evaluate this outcome definitively.

Introduction: Coronavirus disease 2019 (COVID-19) has a high burden on the healthcare system. Prediction models may assist in triaging patients. We aimed to assess the value of several prediction models in COVID-19 patients in the emergency department (ED)., Methods: In this retrospective study, ED patients with COVID-19 were included. Prediction models were selected based on their feasibility. Primary outcome was 30-day mortality, secondary outcomes were 14-day mortality and a composite outcome of 30-day mortality and admission to medium care unit (MCU) or intensive care unit (ICU). The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC)., Results: We included 403 patients. Thirty-day mortality was 23.6%, 14-day mortality was 19.1%, 66 patients (16.4%) were admitted to ICU, 48 patients (11.9%) to MCU, and 152 patients (37.7%) met the composite endpoint. Eleven prediction models were included. The RISE UP score and 4 C mortality scores showed very good discriminatory performance for 30-day mortality (AUC 0.83 and 0.84, 95% CI 0.79-0.88 for both), significantly higher than that of the other models., Conclusion: The RISE UP score and 4 C mortality score can be used to recognise patients at high risk for poor outcome and may assist in guiding decision-making and allocating resources.