Weeks Sharon R, Juillard Catherine J, Monono Martin E, Etoundi Georges A, Ngamby Marquise K, Hyder Adnan A, Stevens Kent A
Johns Hopkins School of Medicine, Baltimore, MD, USA.
World J Surg. 2014 Aug;38(8):1905-11. doi: 10.1007/s00268-014-2496-0.
In the developed world, multiple injury severity scores have been used for trauma patient evaluation and study. However, few studies have supported the effectiveness of different trauma scoring methods in the developing world. The Kampala Trauma Score (KTS) was developed for use in resource-limited settings and has been shown to be a robust predictor of death. This study evaluates the ability of KTS to predict the mortality of trauma patients compared to other trauma scoring systems.
Data were collected on injured patients presenting to Central Hospital of Yaoundé, Cameroon from April 15 to October 15, 2009. The KTS, Injury Severity Score, Revised Trauma Score, Glasgow Coma Scale, and Trauma Injury Severity Score were calculated for each patient. Scores were evaluated as predictors of mortality using logistic regression models. Areas under receiver operating characteristic (ROC) curves were compared.
Altogether, 2855 patients were evaluated with a mortality rate of 6 per 1000. Each score analyzed was a statistically significant predictor of mortality. The area under the ROC for KTS as a predictor of mortality was 0.7748 (95% CI 0.6285-0.9212). There were no statistically significant pairwise differences between ROC areas of KTS and other scores. Similar results were found when the analysis was limited to severe injuries.
This comparison of KTS to other trauma scores supports the adoption of KTS for injury surveillance and triage in resource-limited settings. We show that the KTS is as effective as other scoring systems for predicting patient mortality.
在发达国家,多种损伤严重程度评分已用于创伤患者的评估和研究。然而,很少有研究支持不同创伤评分方法在发展中国家的有效性。坎帕拉创伤评分(KTS)是为资源有限的环境而开发的,已被证明是死亡的有力预测指标。本研究评估了KTS与其他创伤评分系统相比预测创伤患者死亡率的能力。
收集了2009年4月15日至10月15日在喀麦隆雅温得中心医院就诊的受伤患者的数据。为每位患者计算了KTS、损伤严重程度评分、修订创伤评分、格拉斯哥昏迷量表和创伤损伤严重程度评分。使用逻辑回归模型将评分作为死亡率的预测指标进行评估。比较了受试者工作特征(ROC)曲线下的面积。
共评估了2855例患者,死亡率为每1000例中有6例。分析的每个评分都是死亡率的统计学显著预测指标。KTS作为死亡率预测指标的ROC曲线下面积为0.7748(95%CI 0.6285-0.9212)。KTS与其他评分的ROC面积之间没有统计学显著的成对差异。当分析仅限于重伤时,也发现了类似的结果。
KTS与其他创伤评分的比较支持在资源有限的环境中采用KTS进行损伤监测和分诊。我们表明,KTS在预测患者死亡率方面与其他评分系统一样有效。