Predicting Acute Respiratory Distress Syndrome in Severe Blunt Trauma: The Utility of Interleukin-18.

2021 
Background: In trauma, direct pulmonary injury and innate immune response activation primes the lungs for acute respiratory distress syndrome (ARDS). The inflammasome-dependent release of interleukin-18 (IL-18) was recently identified as a key mediator in ARDS pathogenesis, leading us to hypothesize that plasma IL-18 is a diagnostic predictor of ARDS in severe blunt trauma. Patients and Methods: Secondary analysis of the Inflammation and Host Response to Injury database was performed on plasma cytokines collected within 12 hours of severe blunt trauma. Trauma-related cytokines, including IL-18, were compared between patients with and without ARDS and were evaluated for association with ARDS using regression analysis. Threshold cytokine concentrations predictive of ARDS were determined using receiver-operating curve (ROC) analysis. Results: Cytokine analysis of patients without ARDS patients (n = 61) compared with patients with ARDS (n = 19) demonstrated elevated plasma IL-18 concentration in ARDS and IL-18 remained correlated with ARDS on logistic regression after confounder adjustment (p = 0.008). Additionally, ROC analysis revealed IL-18 as a strong ARDS predictor (area under the curve [AUC] = 0.83), with a threshold IL-18 value of 170 pg/mL (Youden index, 0.3). Unlike in patients without ARDS, elevated IL-18 persisted in patients with ARDS during the acute injury phase (p ≤ 0.02). Other trauma-related cytokines did not correlate with ARDS. Conclusions: In severe blunt trauma, IL-18 is a robust predictor of ARDS and remains elevated throughout the acute injury phase. These findings support the use of IL-18 as a key ARDS biomarker, promoting early identification of trauma patients at greater risk of developing ARDS. Timely recognition of ARDS and implementation of advantageous supportive care practices may reduce trauma-related ARDS morbidity and costs.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    24
    References
    0
    Citations
    NaN
    KQI
    []