Fig. 1

Patients non surviving severe trauma exhibit a metabolomic signature. a PLS-DA analyses shows that metabolome is able to discriminate between those patients who survive and those patients who do not survive, with those metabolites contributing to separation shown in the VIP score graph (c). b Heatmap hierarchical clustering analyses using the 25 metabolites with the lowest p value (T-Student test) indicates that there is not a perfect clusterization between groups. PLS-DA cross-validation details (4 components): Accuracy: 0.92, R2: 0.97, Q2: -0.189. The negative value of Q2 means that the model is not all predictive or is overfitted, probably because the low number of not surviving patients