From the Division of Trauma, Burns and Surgical Critical Care, Department of Surgery (S.S., O.H., V.G., J.Nahmias), University of California Irvine Medical Center, Orange; Department of Anesthesiology (C.M.K.), University of Southern California, Los Angeles, California; Department of Anesthesiology (X.L., B.O., M.I.A., E.M., T.M.) and Division of Burns, Trauma and Critical Care (T.S., A.F.), University of Texas Southwestern; Department of Anesthesiology and Pain Management (R.D., J.Navas) and Department of Surgery (G.V., D.D.Y.), University of Miami, Miami, Florida; Department of Surgery (K.M., M.F., T.L.), University of Southern California, Los Angeles; and Institute for Clinical and Translation Sciences (J.R.-O.) and Center for Statistical Consulting (J.R.-O.), University of California, Irvine, California.
J Trauma Acute Care Surg. 2022 Mar 1;92(3):481-488. doi: 10.1097/TA.0000000000003481.
The Trauma and Injury Severity Score (TRISS) uses anatomical and physiologic variables to predict mortality. Elderly (65 years or older) trauma patients have increased mortality and morbidity for a given TRISS, in part because of functional status and comorbidities. These factors are incorporated into the American Society of Anesthesiologists Physical Status (ASA-PS) and National Surgical Quality Improvement Program Surgical Risk Calculator (NSQIP-SRC). We hypothesized scoring tools using comorbidities and functional status to be superior at predicting mortality, hospital length of stay (LOS), and complications in elderly trauma patients undergoing operation.
Four level I trauma centers prospectively collected data on elderly trauma patients undergoing surgery within 24 hours of admission. Using logistic regression, five scoring models were compared: ASA-PS, NSQIP-SRC, TRISS, TRISS-ASA-PS, and TRISS-NSQIP-SRC.Brier scores and area under the receiver operator characteristics curve were calculated to compare mortality prediction. Adjusted R2 and root mean squared error were used to compare LOS and predictive ability for number of complications.
From 122 subjects, 9 (7.4%) died, and the average LOS was 12.9 days (range, 1-110 days). National Surgical Quality Improvement Program Surgical Risk Calculator was superior to ASA-PS and TRISS at predicting mortality (area under the receiver operator characteristics curve, 0.978 vs. 0.768 vs. 0.903; p = 0.007). Furthermore, NSQIP-SRC was more accurate predicting LOS (R2, 25.9% vs. 13.3% vs. 20.5%) and complications (R2, 34.0% vs. 22.6% vs. 29.4%) compared with TRISS and ASA-PS. Adding TRISS to NSQIP-SRC improved predictive ability compared with NSQIP-SRC alone for complications (R2, 35.5% vs. 34.0%; p = 0.046). However, adding ASA-PS or TRISS to NSQIP-SRC did not improve the predictive ability for mortality or LOS.
The NSQIP-SRC, which includes comorbidities and functional status, had superior ability to predict mortality, LOS, and complications compared with TRISS alone in elderly trauma patients undergoing surgery.
Prognostic and Epidemiologic; Level III.
创伤和损伤严重程度评分(TRISS)使用解剖学和生理学变量来预测死亡率。对于给定的 TRISS,老年(65 岁及以上)创伤患者的死亡率和发病率更高,部分原因是功能状态和合并症。这些因素被纳入美国麻醉医师协会身体状况(ASA-PS)和国家手术质量改进计划手术风险计算器(NSQIP-SRC)。我们假设使用合并症和功能状态的评分工具在预测死亡率、住院时间(LOS)和接受手术的老年创伤患者的并发症方面更具优势。
四家一级创伤中心前瞻性收集了在入院后 24 小时内接受手术的老年创伤患者的数据。使用逻辑回归,比较了五种评分模型:ASA-PS、NSQIP-SRC、TRISS、TRISS-ASA-PS 和 TRISS-NSQIP-SRC。计算 Brier 分数和接受者操作特征曲线下面积以比较死亡率预测。调整 R2 和均方根误差用于比较 LOS 和并发症数量的预测能力。
从 122 名患者中,有 9 名(7.4%)死亡,平均 LOS 为 12.9 天(范围为 1-110 天)。与 ASA-PS 和 TRISS 相比,国家手术质量改进计划手术风险计算器在预测死亡率方面更具优势(接受者操作特征曲线下面积,0.978 比 0.768 比 0.903;p=0.007)。此外,与 TRISS 和 ASA-PS 相比,NSQIP-SRC 更准确地预测 LOS(R2,25.9%比 13.3%比 20.5%)和并发症(R2,34.0%比 22.6%比 29.4%)。与 NSQIP-SRC 相比,将 TRISS 添加到 NSQIP-SRC 可改善并发症的预测能力(R2,35.5%比 34.0%;p=0.046)。然而,将 ASA-PS 或 TRISS 添加到 NSQIP-SRC 并不能提高死亡率或 LOS 的预测能力。
与单独使用 TRISS 相比,在接受手术的老年创伤患者中,包含合并症和功能状态的 NSQIP-SRC 具有更好的预测死亡率、LOS 和并发症的能力。
预后和流行病学;III 级。