caa a22 4500 605467234 CHVBK 20210128100310.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s10049-015-0055-3 doi (NATIONALLICENCE)springer-10.1007/s10049-015-0055-3 Predicting in-hospital mortality using routine parameters in unselected nonsurgical emergency department patients [Elektronische Daten] [A. Slagman, J. Searle, J.O. Vollert, C. Müller, R. Muller, R. Somasundaram, M. Möckel] Vorhersage der intrahospitalen Mortalität unselektierter internistischer Notfallpatienten anhand von Routineparametern Background: To assure adequate and efficient treatment in the emergency department (ED) despite increasing patient numbers, early risk stratification might be helpful for directing resource allocation. Objective: To determine whether routine clinical data can predict in-hospital mortality in nonsurgical ED patients and to specifically identify the best predictive parameters. Materials and methods: This retrospective cohort study investigated 34,333nonsurgical adult patients who attended one of the two participating EDs in Berlin, Germany, within 1year. Routine clinical data were analysed for their potential to predict in-hospital mortality using logistic regression as well as classification and regression tree (CART) analysis. A validation dataset contained 35,646patients of the following year. Results: In-hospital mortality was 1.8 % (634/34,333). C-reactive protein (CRP) and red cell distribution width (RDW) were the best predictors of mortality. A model with nine predictors (CRP, RDW, age, potassium, sodium, WBC, platelets, RBC and creatinine) achieved an area under the receiver operating characteristic curve (AUROC) of 0.870(95 % confidence interval, CI:0.857-0.883). A three-marker model (CRP, RDW, age) resulted in an AUROC of 0.866(95 % CI:0.853-0.878). In the independent validation dataset the AUROC for this three-marker model was 0.837(95 % CI:0.825-0.850). CART analysis corroborated the importance of CRP and RDW, and a clinical algorithm for risk stratification was developed (Emergency Processes in Clinical Structures, EPICS score). Conclusion: Two different statistical procedures and independent validation revealed similar results, suggesting a combination of CRP and RDW as a score (EPICS score) for early identification of high-risk patients. This might be particularly helpful in overcrowded situations and where resources are limited. The suggested score should be validated and potentially adapted to diverse ED settings and patient populations in international multicentre trials. Springer-Verlag Berlin Heidelberg, 2015 Risk stratification nationallicence C-reactive protein nationallicence ROC curve nationallicence Resources nationallicence Adult nationallicence Risikostratifizierung nationallicence C-reaktives Protein nationallicence ROC-Kurve nationallicence Ressourcen nationallicence Erwachsene nationallicence APACHEII : Acute Physiology and Chronic Health EvaluationII nationallicence CART : classification and regression tree nationallicence CRP : C-reactive protein nationallicence EPICS : Emergency Processes in Clinical Structures nationallicence ESI : Emergency Severity Index nationallicence GCS : Glasgow Coma Scale nationallicence HIS : hospital information system nationallicence MTS : Manchester Triage System nationallicence RAPS : Rapid Acute Physiology Score nationallicence RDW : red cell distribution width nationallicence REMS : Rapid Emergency Medicine Score nationallicence SOP : standard operating procedure nationallicence Slagman A. Division of Emergency Medicine, Charité University Medicine, North Campi (CVK, CCM), Augustenburger Platz 1, 13353, Berlin, Germany aut Searle J. Division of Emergency Medicine, Charité University Medicine, North Campi (CVK, CCM), Augustenburger Platz 1, 13353, Berlin, Germany aut Vollert J.O. Division of Emergency Medicine, Charité University Medicine, North Campi (CVK, CCM), Augustenburger Platz 1, 13353, Berlin, Germany aut Müller C. Department of Laboratory Medicine, Charité University Medicine, Berlin, Germany aut Muller R. James Cook University, Townsville, Australia aut Somasundaram R. Division of Emergency Medicine (CBF), Berlin, Germany aut Möckel M. Division of Emergency Medicine, Charité University Medicine, North Campi (CVK, CCM), Augustenburger Platz 1, 13353, Berlin, Germany aut Notfall + Rettungsmedizin Springer Berlin Heidelberg 18/6(2015-10-01), 501-509 1434-6222 18:6<501 2015 18 10049 https://doi.org/10.1007/s10049-015-0055-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10049-015-0055-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Slagman A. Division of Emergency Medicine, Charité University Medicine, North Campi (CVK, CCM), Augustenburger Platz 1, 13353, Berlin, Germany aut NATIONALLICENCE 700 1- Searle J. Division of Emergency Medicine, Charité University Medicine, North Campi (CVK, CCM), Augustenburger Platz 1, 13353, Berlin, Germany aut NATIONALLICENCE 700 1- Vollert J.O. Division of Emergency Medicine, Charité University Medicine, North Campi (CVK, CCM), Augustenburger Platz 1, 13353, Berlin, Germany aut NATIONALLICENCE 700 1- Müller C. Department of Laboratory Medicine, Charité University Medicine, Berlin, Germany aut NATIONALLICENCE 700 1- Muller R. James Cook University, Townsville, Australia aut NATIONALLICENCE 700 1- Somasundaram R. Division of Emergency Medicine (CBF), Berlin, Germany aut NATIONALLICENCE 700 1- Möckel M. Division of Emergency Medicine, Charité University Medicine, North Campi (CVK, CCM), Augustenburger Platz 1, 13353, Berlin, Germany aut NATIONALLICENCE 773 0- Notfall + Rettungsmedizin Springer Berlin Heidelberg 18/6(2015-10-01), 501-509 1434-6222 18:6<501 2015 18 10049