Corral Torres Ervigio, Hernández-Tejedor Alberto, Millán Estañ Pablo, Valiente Fernández Marcos, Bringas Bollada María, Pérez Díaz Dolores, Monforte-Escobar Fernando, Vejo Gutiérrez Javier, Orejón García Lidia, Delgado Pascual Ana, Rey Valcárcel Cristina, Camacho Leis Carmen
SAMUR-Protección Civil, Madrid, España.
Servicio de Medicina Intensiva, Hospital Universitario La Paz, Madrid, España.
Emergencias. 2023 Apr;35(2):90-96. doi: 10.55633/s3me/E075.2023.
Patients with severe or potentially severe trauma must be identified early, a challenge in prehospital settings. This study aimed to analyze the possible diagnostic and prognostic usefulness of analytical markers recorded in the early moments of care.
Observational study of information extracted from the prospective multicenter Code Trauma database for 2016-2019, excluding data for isolated head injuries. Using the New Injury Severity Score (NISS), we classified cases into 4 levels of severity. NISS and mortality were considered the dependent variables in inferential analyses. We calculated the areas under receiver operating characteristic curves, identified optimal cutoff points (Youden index), and calculated positive (PPV) and negative predictive values..
Of the 1039 trauma patients in the registry, 709 were included in the study. Their mean (SD) age was 40.4 (17.3) years, and 77.3% were men. Motorcycle accidents were the most common causes of trauma (in 21%), and mortality was 12.1%. Lactate concentration, pH, PCO2, hemoglobin concentration, hematocrit, and blood sugar were significantly associated with severity and mortality. The PPVs corresponding to pH for the 4 NISS score groups (34-41, 42-49, 50-59, and $ 60) and mortality, respectively, were 61.2, 64.1, 70.7, 62.2, and 66.6. The PPVs of traditionally used clinical variables were lower.
Patients with more severe trauma had lower pH values and higher PCO2, lactate, and base excess values. PCO2, pH, and blood sugar findings were the best predictors of severity. Metabolic variables are better predictors than traditionally recorded hemodynamic variables.
必须尽早识别出严重或潜在严重创伤的患者,这在院前环境中是一项挑战。本研究旨在分析在护理早期记录的分析标志物的可能诊断和预后效用。
对从2016 - 2019年前瞻性多中心创伤编码数据库中提取的信息进行观察性研究,排除孤立性头部损伤的数据。使用新损伤严重度评分(NISS),我们将病例分为4个严重程度级别。在推断性分析中,将NISS和死亡率视为因变量。我们计算了受试者工作特征曲线下的面积,确定了最佳截断点(约登指数),并计算了阳性预测值(PPV)和阴性预测值。
登记的1039例创伤患者中,709例纳入研究。他们的平均(标准差)年龄为40.4(17.3)岁,77.3%为男性。摩托车事故是创伤最常见的原因(占21%),死亡率为12.1%。乳酸浓度、pH值、PCO2、血红蛋白浓度、血细胞比容和血糖与严重程度和死亡率显著相关。4个NISS评分组(34 - 41、42 - 49、50 - 59和≥60)对应的pH值和死亡率的PPV分别为61.2、64.1、70.7、62.2和66.6。传统使用的临床变量的PPV较低。
创伤更严重的患者pH值较低,PCO2、乳酸和碱剩余值较高。PCO2、pH值和血糖结果是严重程度的最佳预测指标。代谢变量比传统记录的血流动力学变量是更好的预测指标。