一种新型急诊手术 acuity 评分（ESAS）的推导与验证。
Derivation and validation of a novel Emergency Surgery Acuity Score (ESAS).
作者信息
Sangji Naveen F, Bohnen Jordan D, Ramly Elie P, Yeh Daniel D, King David R, DeMoya Marc, Butler Kathryn, Fagenholz Peter J, Velmahos George C, Chang David C, Kaafarani Haytham M A
机构信息
From the Division of Trauma, Emergency Surgery, and Surgical Critical Care (N.F.S., J.D.B., E.P.R., D.D.Y., D.R.K., M.D., K.B., P.J.F., G.C.V., H.M.A.K.), Department of Surgery, and Codman Center for Clinical Effectiveness in Surgery (N.F.S., D.C.C., H.M.A.K.), Massachusetts General Hospital, Boston, Massachussetts.
出版信息
J Trauma Acute Care Surg. 2016 Aug;81(2):213-20. doi: 10.1097/TA.0000000000001059.
BACKGROUND
There currently exists no preoperative risk stratification system for emergency surgery (ES). We sought to develop an Emergency Surgery Acuity Score (ESAS) that helps predict perioperative mortality in ES patients.
METHODS
Using the 2011 American College of Surgeons' National Surgical Quality Improvement Program (ACS-NSQIP) database (derivation cohort), we identified all surgical procedures that were classified as "emergent." A three-step methodology was then performed. First, multiple logistic regression models were created to identify independent predictors (e.g., patient demographics, comorbidities, and preoperative laboratory variables) of 30-day mortality in ES. Second, based on the relative impact of each identified predictor (i.e., odds ratio), using weighted averages, a novel score was derived. Third, using the 2012 ACS-NSQIP database (validation cohort), the score was validated by calculating its C statistic and evaluating its ability to predict 30-day mortality.
RESULTS
From 280,801 NSQIP cases, 18,439 ES cases were analyzed, of which 1,598 (8.7%) resulted in death at 30 days. The multiple logistic regression analyses identified 22 independent predictors of mortality. Based on the relative impact of these predictors, ESAS was derived with a total score range of 0 to 29. ESAS had a C statistic of 0.86; the probability of death at 30 days gradually increased from 0% to 36% then 100% at scores of 0, 11, and 22, respectively. In the validation phase, 19,552 patients were included, the mortality rate was 7.2%, and the ESAS C statistic stayed at 0.86.
CONCLUSION
We have therefore developed and validated a novel score, ESAS, that accurately predicts mortality in ES patients. Such a score could prove useful for (1) preoperative patient counseling, (2) identification of patients needing close postoperative monitoring, and (3) risk adjustment in any efforts at benchmarking the quality of ES.
LEVEL OF EVIDENCE
Prognostic/epidemiologic study, level III.
背景
目前尚无针对急诊手术（ES）的术前风险分层系统。我们试图开发一种急诊手术 acuity 评分（ESAS），以帮助预测 ES 患者的围手术期死亡率。
方法
利用 2011 年美国外科医师学会国家外科质量改进计划（ACS-NSQIP）数据库（推导队列），我们确定了所有被归类为“急诊”的手术程序。然后进行了三步方法。首先，创建多元逻辑回归模型以识别 ES 患者 30 天死亡率的独立预测因素（例如患者人口统计学、合并症和术前实验室变量）。其次，根据每个已识别预测因素的相对影响（即比值比），使用加权平均值得出一个新的评分。第三，使用 2012 年 ACS-NSQIP 数据库（验证队列），通过计算其 C 统计量并评估其预测 30 天死亡率的能力来验证该评分。
结果
在 280,801 例 NSQIP 病例中，分析了 18,439 例 ES 病例，其中 1,598 例（8.7%）在 30 天时死亡。多元逻辑回归分析确定了 22 个死亡率的独立预测因素。根据这些预测因素的相对影响，得出 ESAS，总分范围为 0 至 29。ESAS 的 C 统计量为 0.86；30 天时的死亡概率在评分分别为 0、11 和 22 时从 0%逐渐增加到 36%，然后为 100%。在验证阶段，纳入了 19,552 名患者，死亡率为 7.2%，ESAS 的 C 统计量保持在 0.86。
结论
因此，我们开发并验证了一种新的评分 ESAS，它能准确预测 ES 患者的死亡率。这样的评分可能对（1）术前患者咨询、（2）识别需要术后密切监测的患者以及（3）在任何评估 ES 质量的努力中进行风险调整有用。
证据水平
预后/流行病学研究，III 级。
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