Predictive Modeling and Inflammatory Biomarkers in Rats With Lung Contusion and Gastric Aspiration

Abstract

This study uses statistical predictive modeling and hierarchical cluster analyses to examine inflammatory mediators and cells in bronchoalveolar lavage (BAL) as putative biomarkers in rats with blunt trauma lung contusion (LC), gastric aspiration (combined acid and small gastric food particles, CASP), or a combination of the two. Specific parameters assessed in the innate pulmonary inflammatory response were leukocytes, macrophages, and polymorphonuclear neutrophils (PMNs) in BAL; whole lung myeloperoxidase activity; and a series of cytokines or chemokines present in BAL at 5 or 24 hours after injury: tumor necrosis factor-alpha, interleukin (IL)-1beta, IL-6, interferon-gamma, IL-10, macrophage inflammatory protein-2, cytokine-induced neutrophil chemoattractant-1, and monocyte chemoattractant protein-1. Rats with LC, CASP, LC + CASP all had severe lung injury compared with uninjured controls based on decreased arterial oxygenation or increased BAL albumin at 5 or 24 hours postinsult. However, the injury groups had distinct overall patterns of inflammation that allowed them to be discriminated accurately by hierarchical cluster analysis (29 of 30 and 35 of 37 rats were correctly classified in hierarchical clusters at 5 and 24 hours, respectively). Moreover, predictive analyses based on an extension of standard receiver-operator characteristic methodology discriminated individual animals and groups with similar high accuracy based on a maximum of two inflammatory parameters per group (29 of 30 and 36 of 37 rats were correctly classified at 5 hours and 24 hours, respectively). These results support the possibility that inflammatory biomarker profiles could be developed in the future to improve the diagnosis and management of trauma patients with unwitnessed (occult) gastric aspiration who have an increased risk of clinical acute lung injury or the acute respiratory distress syndrome.