Infection biomarkers at intensive care units - Araújo, Rúben Alexandre Dinis (2024)
It is relevant to discover infection biomarkers, especially for critically ill patients in intensive care units (ICU), as these patients often present non-infectious inflammatory processes that obscure typical infectious markers. This study focused on 20 ICU patients, half of whom had acquired bacterial blood infections (bacteremia). Due to the significance of inflammatory processes in these patients, it was evaluated how 21 serum cytokines could be used to develop predictive models for bacteremia. Feature selection using a Gain Information algorithm allowed for the construction of an excellent Naïve Bayes model, achieving an AUC of 0.950. These promising results strongly support future studies with larger cohorts, to further evaluate these types of platforms for infection diagnosis in such critical populations.