Trajectories of Survivors and Non-Survivors Post-burn Injury.
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OBJECTIVE: To gain insights into the systemic response after burn injury, we aimed to characterize the phases of inflammatory and metabolic trajectories in survivors and non-survivors. BACKGROUND: Survival after burn injuries has improved over the past few decades. However, a large proportion of the patients do not survive. METHODS: This was a single-center cohort study. We included patients (aged ≥ 18 years) with burn injuries (≥ 10% total body surface area; TBSA) admitted to our provincial burn center. Clinical outcomes, laboratory measures, and inflammatory biomarkers were compared among survivors, early non-survivors (died ≤4 days post-injury), and late non-survivors (died ≥5 days post-injury). RESULTS: We studied 872 patients with a median age of 49 (Interquartile Range, IQR: 35-63) years and a median percent TBSA burn of 19% (IQR: 13-34) TBSA burn for survivors (n=705; 81%), early non-survivors (n=99; 11%), and late non-survivors (n=68; 8%). The median ages were 46 (IQR: 33-59) years for survivors, 62 (IQR: 46-73) years for early non-survivors, and 67 (IQR: 54-76) years for late non-survivors (P<0.0001). The median % TBSA burn was 17 (IQR: 13-26) for survivors, 67 (IQR: 43-88) for early non-survivors, and 27 (IQR: 18-44) for late non-survivors (P<0.0001). Non-survivors exhibited significantly elevated biomarkers compared to survivors, with distinct metabolic and inflammatory profiles, including increased IL-1β, IL-8, TNF-α, and IL-10. Late non-survivors experienced higher complication rates (P<0.01), with significant differences in inflammatory and metabolic responses over time. CONCLUSIONS: Survivors and non-survivors showed distinct post-injury inflammatory and metabolic responses. Identifying the relationship between concomitant immune activation and suppression among survivors and non-survivors may improve patient outcomes by defining and altering inflammatory trajectories. Elucidating the differences in trajectories between early and late non-survivors could allow for the prediction and identification of patients at risk of mortality.
