BACKGROUND: Early warning scores (EWS) may aid the prediction of major adverse events in hospitalized patients. Recently, an expanded EWS was introduced in the Netherlands. The aim of this study was to assess the relationship between this EWS and the occurrence of major adverse clinical events during hospitalization of patients admitted to a general and trauma surgery ward. METHODS: This was a prospective cohort study of consecutive patients admitted to the general and trauma surgery ward of a university medical centre (March-September 2009). Follow-up was limited to the time the patient was hospitalized. Logistic regression analysis was used to assess the relationship between the EWS and the occurrence of the composite endpoint consisting of death, reanimation, unexpected intensive care unit admission, emergency surgery and severe complications. Performance of the EWS was analysed using sensitivity, specificity, predictive values and receiver operating characteristic (ROC) curves. RESULTS: A total of 572 patients were included. During a median follow-up of 4 days, 46 patients (8.0 per cent) reached the composite endpoint (two deaths, two reanimations, 17 intensive care unit admissions, 44 severe complications, one emergency operation). An EWS of at least 3, adjusted for baseline American Society of Anesthesiology classification, was associated with a significantly higher risk of reaching the composite endpoint (odds ratio 11·3, 95 per cent confidence interval (c.i.) 5·5 to 22·9). The area under the ROC curve was 0·87 (95 per cent c.i. 0·81 to 0·93). When considering an EWS of at least 3 to be a positive test result, sensitivity was 74 per cent and specificity was 82 per cent. CONCLUSION: An EWS of 3 or more is an independent predictor of major adverse events in patients admitted to a general and trauma surgery ward.
BACKGROUND: Early warning scores (EWS) may aid the prediction of major adverse events in hospitalized patients. Recently, an expanded EWS was introduced in the Netherlands. The aim of this study was to assess the relationship between this EWS and the occurrence of major adverse clinical events during hospitalization of patients admitted to a general and trauma surgery ward. METHODS: This was a prospective cohort study of consecutive patients admitted to the general and trauma surgery ward of a university medical centre (March-September 2009). Follow-up was limited to the time the patient was hospitalized. Logistic regression analysis was used to assess the relationship between the EWS and the occurrence of the composite endpoint consisting of death, reanimation, unexpected intensive care unit admission, emergency surgery and severe complications. Performance of the EWS was analysed using sensitivity, specificity, predictive values and receiver operating characteristic (ROC) curves. RESULTS: A total of 572 patients were included. During a median follow-up of 4 days, 46 patients (8.0 per cent) reached the composite endpoint (two deaths, two reanimations, 17 intensive care unit admissions, 44 severe complications, one emergency operation). An EWS of at least 3, adjusted for baseline American Society of Anesthesiology classification, was associated with a significantly higher risk of reaching the composite endpoint (odds ratio 11·3, 95 per cent confidence interval (c.i.) 5·5 to 22·9). The area under the ROC curve was 0·87 (95 per cent c.i. 0·81 to 0·93). When considering an EWS of at least 3 to be a positive test result, sensitivity was 74 per cent and specificity was 82 per cent. CONCLUSION: An EWS of 3 or more is an independent predictor of major adverse events in patients admitted to a general and trauma surgery ward.
Authors: Bartlomiej Bartkowiak; Ashley M Snyder; Andrew Benjamin; Andrew Schneider; Nicole M Twu; Matthew M Churpek; Kevin K Roggin; Dana P Edelson Journal: Ann Surg Date: 2019-06 Impact factor: 12.969
Authors: Mariska Weenk; Harry van Goor; Maartje van Acht; Lucien Jlpg Engelen; Tom H van de Belt; Sebastian J H Bredie Journal: PLoS One Date: 2018-02-12 Impact factor: 3.240
Authors: Louise S van Galen; Casper C Dijkstra; Jeroen Ludikhuize; Mark H H Kramer; Prabath W B Nanayakkara Journal: PLoS One Date: 2016-08-05 Impact factor: 3.240