BACKGROUND: EWS is frequently used to monitor acute admissions requiring emergency surgery. This study examined preoperative early warning scoring (EWS) and its ability to predict mortality and critical care admission. Postoperative EWS was also evaluated as a predictor of mortality. METHODS: Preoperative EWS, age, physiologic and operative severity (POSSUM) scores, ASA grade, and serology were compared in 280 patients undergoing emergency surgery. RESULTS: Two hundred eighty patients were identified with a mortality of 15%. Among the physiological scoring systems, ASA grade and POSSUM scores were the best predictors of mortality (AUC values of 0.81). EWS, APACHE II, and age were the next best predictors (AUC values of 0.70). Postoperative APACHE II and EWS both predicted mortality. EWS on day 2 postoperatively was the best overall predictor of mortality of all the variables studied (AUC value of 0.83). Survival between patients with "improving or stable" EWS and those with "deteriorating or failing to improve" EWS was also found to be significantly different (P < 0.001). In addition, both EWS on admission and EWS 1 h preoperatively were found to predict critical care requirement postoperatively (AUC value of 0.78). CONCLUSIONS: EWS can predict the need for critical care admission and mortality following emergency surgery. In particular, the progression of EWS preoperatively, that is, whether scores improve or deteriorate, is a highly significant factor in predicting survival following emergency surgery. These findings support the use of EWS in monitoring the acute surgical patient.
BACKGROUND: EWS is frequently used to monitor acute admissions requiring emergency surgery. This study examined preoperative early warning scoring (EWS) and its ability to predict mortality and critical care admission. Postoperative EWS was also evaluated as a predictor of mortality. METHODS: Preoperative EWS, age, physiologic and operative severity (POSSUM) scores, ASA grade, and serology were compared in 280 patients undergoing emergency surgery. RESULTS: Two hundred eighty patients were identified with a mortality of 15%. Among the physiological scoring systems, ASA grade and POSSUM scores were the best predictors of mortality (AUC values of 0.81). EWS, APACHE II, and age were the next best predictors (AUC values of 0.70). Postoperative APACHE II and EWS both predicted mortality. EWS on day 2 postoperatively was the best overall predictor of mortality of all the variables studied (AUC value of 0.83). Survival between patients with "improving or stable" EWS and those with "deteriorating or failing to improve" EWS was also found to be significantly different (P < 0.001). In addition, both EWS on admission and EWS 1 h preoperatively were found to predict critical care requirement postoperatively (AUC value of 0.78). CONCLUSIONS: EWS can predict the need for critical care admission and mortality following emergency surgery. In particular, the progression of EWS preoperatively, that is, whether scores improve or deteriorate, is a highly significant factor in predicting survival following emergency surgery. These findings support the use of EWS in monitoring the acute surgical patient.
Authors: Chieh Yang Koo; Joseph A Hyder; Jonathan P Wanderer; Matthias Eikermann; Satya Krishna Ramachandran Journal: World J Surg Date: 2015-01 Impact factor: 3.352
Authors: Morten Vester-Andersen; Tina Waldau; Jørn Wetterslev; Morten Hylander Møller; Jacob Rosenberg; Lars Nannestad Jørgensen; Inger Gillesberg; Henrik Loft Jakobsen; Egon Godthåb Hansen; Lone Musaeus Poulsen; Jan Skovdal; Ellen Kristine Søgaard; Morten Bestle; Jesper Vilandt; Iben Rosenberg; Rasmus Ehrenfried Berthelsen; Jens Pedersen; Mogens Rørbæk Madsen; Thomas Feurstein; Malene Just Busse; Johnny D H Andersen; Christian Maschmann; Morten Rasmussen; Christian Jessen; Lasse Bugge; Helle Ørding; Ann Merete Møller Journal: Trials Date: 2013-02-02 Impact factor: 2.279
Authors: Michael J Jones; Christopher P Neal; Wee Sing Ngu; Ashley R Dennison; Giuseppe Garcea Journal: Langenbecks Arch Surg Date: 2017-04-22 Impact factor: 3.445