Prediction of Multiple Infections After Severe Burn Trauma: a Prospective Cohort Study - Yan, Shuangchun (Ann Surg, 2015)
OBJECTIVE: To develop predictive models for early triage of burn patients based on hyper-susceptibility to repeated infections. BACKGROUND: Infection remains a major cause of mortality and morbidity after severe trauma, demanding new strategies to combat infections. Models for infection prediction are lacking. METHODS: Secondary analysis of 459 burn patients (≥16 years old) with ≥20% total body surface area burns recruited from six US burn centers. We compared blood transcriptomes with a 180-h cut-off on the injury-to-transcriptome interval of 47 patients (≤1 infection episode) to those of 66 hyper-susceptible patients (multiple [≥2] infection episodes [MIE]). We used LASSO regression to select biomarkers and multivariate logistic regression to built models, accuracy of which were assessed by area under receiver operating characteristic curve (AUROC) and cross-validation. RESULTS: Three predictive models were developed covariates of: (1) clinical characteristics; (2) expression profiles of 14 genomic probes; (3) combining (1) and (2). The genomic and clinical models were highly predictive of MIE status (AUROC(Genomic) = 0.946 [95% CI, 0.906–0.986]); AUROC(Clinical) = 0.864 [CI, 0.794–0.933]; AUROC(Genomic)/AUROC(Clinical) P = 0.044). Combined model has an increased AUROC(Combined) of 0.967 (CI, 0.940–0.993) compared to the individual models (AUROC(Combined)/AUROC(Clinical) P = 0.0069). Hyper-susceptible patients show early alterations in immune-related signaling pathways, epigenetic modulation and chromatin remodeling. CONCLUSIONS: Early triage of burn patients more susceptible to infections can be made using clinical characteristics and/or genomic signatures. Genomic signature suggests new insights into the pathophysiology of hyper-susceptibility to infection may lead to novel potential therapeutic or prophylactic targets.