Discriminatory plasma biomarkers predict specific clinical phenotypes of necrotizing soft-tissue infections

BACKGROUND: Necrotizing soft-tissue infections (NSTIs) are rapidly progressing infections frequently complicated by septic shock and associated with high mortality. Early diagnosis is critical for patient outcome, but challenging due to vague initial symptoms. Here, we identified predictive biomarke...

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Detalles Bibliográficos
Autores principales: Palma Medina, Laura M., Rath, Eivind, Jahagirdar, Sanjeevan, Bruun, Trond, Madsen, Martin B., Strålin, Kristoffer, Unge, Christian, Hansen, Marco Bo, Arnell, Per, Nekludov, Michael, Hyldegaard, Ole, Lourda, Magda, dos Santos, Vitor A.P. Martins, Saccenti, Edoardo, Skrede, Steinar, Svensson, Mattias, Norrby-Teglund, Anna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Clinical Investigation 2021
Materias:
Clinical Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279592/
https://www.ncbi.nlm.nih.gov/pubmed/34263738
http://dx.doi.org/10.1172/JCI149523
Descripción
Sumario:BACKGROUND: Necrotizing soft-tissue infections (NSTIs) are rapidly progressing infections frequently complicated by septic shock and associated with high mortality. Early diagnosis is critical for patient outcome, but challenging due to vague initial symptoms. Here, we identified predictive biomarkers for NSTI clinical phenotypes and outcomes using a prospective multicenter NSTI patient cohort. METHODS: Luminex multiplex assays were used to assess 36 soluble factors in plasma from NSTI patients with positive microbiological cultures (n = 251 and n = 60 in the discovery and validation cohorts, respectively). Control groups for comparative analyses included surgical controls (n = 20), non-NSTI controls (i.e., suspected NSTI with no necrosis detected upon exploratory surgery, n = 20), and sepsis patients (n = 24). RESULTS: Thrombomodulin was identified as a unique biomarker for detection of NSTI (AUC, 0.95). A distinct profile discriminating mono- (type II) versus polymicrobial (type I) NSTI types was identified based on differential expression of IL-2, IL-10, IL-22, CXCL10, Fas-ligand, and MMP9 (AUC >0.7). While each NSTI type displayed a distinct array of biomarkers predicting septic shock, granulocyte CSF (G-CSF), S100A8, and IL-6 were shared by both types (AUC >0.78). Finally, differential connectivity analysis revealed distinctive networks associated with specific clinical phenotypes. CONCLUSIONS: This study identifies predictive biomarkers for NSTI clinical phenotypes of potential value for diagnostic, prognostic, and therapeutic approaches in NSTIs. TRIAL REGISTRATION: ClinicalTrials.gov NCT01790698. FUNDING: Center for Innovative Medicine (CIMED); Region Stockholm; Swedish Research Council; European Union; Vinnova; Innovation Fund Denmark; Research Council of Norway; Netherlands Organisation for Health Research and Development; DLR Federal Ministry of Education and Research; and Swedish Children’s Cancer Foundation.

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