Department of Hepatobiliary and Pancreatic Surgery, Leicester General Hospital, Leicester, United Kingdom.
J Surg Res. 2010 Apr;159(2):729-34. doi: 10.1016/j.jss.2008.08.013. Epub 2008 Nov 12.
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.
Preoperative EWS, age, physiologic and operative severity (POSSUM) scores, ASA grade, and serology were compared in 280 patients undergoing emergency surgery.
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).
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.
EWS 常用于监测需要紧急手术的急性入院患者。本研究检查了术前早期预警评分(EWS)及其预测死亡率和重症监护病房入院的能力。还评估了术后 EWS 作为死亡率的预测指标。
比较了 280 例接受急诊手术的患者的术前 EWS、年龄、生理和手术严重程度(POSSUM)评分、ASA 分级和血清学。
确定了 280 例患者,死亡率为 15%。在生理评分系统中,ASA 分级和 POSSUM 评分是死亡率的最佳预测指标(AUC 值为 0.81)。EWS、APACHE II 和年龄是下一个最佳预测指标(AUC 值为 0.70)。术后 APACHE II 和 EWS 均预测死亡率。术后第 2 天的 EWS 是所有研究变量中预测死亡率的最佳总体指标(AUC 值为 0.83)。发现“改善或稳定”EWS 的患者与“恶化或未能改善”EWS 的患者之间的生存率也存在显著差异(P < 0.001)。此外,入院时的 EWS 和术前 1 小时的 EWS 均预测术后重症监护的需求(AUC 值为 0.78)。
EWS 可预测急诊手术后的重症监护病房入院和死亡率。特别是,术前 EWS 的进展,即评分是否改善或恶化,是预测急诊手术后生存的一个非常重要的因素。这些发现支持在监测急性外科患者时使用 EWS。