• Corral TorresErvigioESAMUR-Protección Civil, Madrid, España., Alberto Hernández-Tejedor, Pablo Millán Estañ, Marcos Valiente Fernández, María Bringas Bollada, Dolores Pérez Díaz, Fernando Monforte-Escobar, Javier Vejo Gutiérrez, Lidia Orejón García, Ana Delgado Pascual, Cristina Rey Valcárcel, and Camacho LeisCarmenCSAMUR-Protección Civil, Madrid, España..
• SAMUR-Protección Civil, Madrid, España.
• Emergencias. 2023 Apr 1; 35 (2): 909690-96.

ObjectivesPatients 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.Material And MethodsObservational 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..ResultsOf 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.ConclusionPatients 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.

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