Hahamyan Henrik A, Archer Allen D, Heard Matthew A, Dockery Nathan A, Wahlquist Amy E, Burns J Bracken
Quillen College of Medicine, East Tennessee State University, Johnson City, TN, USA.
Department of Surgery, East Tennessee State University, Johnson City, TN, USA.
Am Surg. 2025 Aug;91(8):1238-1243. doi: 10.1177/00031348251350990. Epub 2025 Jun 10.
BackgroundTo assess the strength of the Geriatric Trauma Outcome Score (GTOS) in predicting mortality in geriatric trauma patients using a nationally representative sample.MethodsData from the National Trauma Data Bank were collected retrospectively from 2017 and 2018 for patients aged 65 and older (N = 487,317). Age, injury severity score (ISS), transfusion status, and hospital discharge status (survived vs deceased) were extracted. GTOS was then calculated for each patient. Simple logistic regression models were used to model hospital discharge status with GTOS and each component. Receiver-operating characteristic (ROC) curves were created using the predicted probabilities from the logistic models, and the area under the curve (AUC) for each model was calculated.ResultsPatients had a mean (SD) GTOS of 101.85 (19.53), age of 77.06 (7.20) years, and ISS of 9.75 (6.90). Very few (2%) patients had a blood transfusion within 24 hours of admission, and the overall survival rate was 96%. All models showed statistical significance in predicting discharge status ( < 0.0001) with AUCs of 0.5436 (age), 0.5727 (receipt of blood), 0.7979 (ISS), and 0.8145 (GTOS). When comparing models from each component to that of GTOS, GTOS remained more predictive than each individual component ( < 0.0001).DiscussionAfter analyzing our models based on a nationally representative trauma data bank, GTOS predicted mortality better than each of its individual components. Therefore, GTOS is an appropriate tool to predict mortality among geriatric trauma patients and should be considered for applications such as informing goals-of-care or trauma transfer decision-making.
背景
使用具有全国代表性的样本评估老年创伤结局评分(GTOS)预测老年创伤患者死亡率的能力。
方法
回顾性收集2017年和2018年来自国家创伤数据库中65岁及以上患者的数据(N = 487,317)。提取年龄、损伤严重程度评分(ISS)、输血状态和出院状态(存活与死亡)。然后为每位患者计算GTOS。使用简单逻辑回归模型以GTOS及其每个组成部分为变量对出院状态进行建模。利用逻辑模型的预测概率创建受试者工作特征(ROC)曲线,并计算每个模型的曲线下面积(AUC)。
结果
患者的GTOS平均(标准差)为101.85(19.53),年龄为77.06(7.20)岁,ISS为9.75(6.90)。入院后24小时内接受输血的患者极少(2%),总体生存率为96%。所有模型在预测出院状态方面均具有统计学意义(<0.0001),AUC分别为0.5436(年龄)、0.5727(输血情况)、0.7979(ISS)和0.8145(GTOS)。当将每个组成部分的模型与GTOS模型进行比较时,GTOS的预测能力仍高于每个单独的组成部分(<0.0001)。
讨论
在基于全国代表性创伤数据库分析我们的模型后,GTOS在预测死亡率方面比其各个单独组成部分表现更好。因此,GTOS是预测老年创伤患者死亡率的合适工具,应考虑将其应用于诸如确定治疗目标或创伤转运决策等方面。