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A Pro-Inflammatory Biomarker-Profile Predicts Amputation-Free Survival in Patients with Severe Limb Ischemia

Patients with Severe Limb Ischemia (SLI) have a high risk of amputation and mortality. Here, we investigated a panel of serum biomarkers with the aim of identifying biomarkers for major events and mechanisms that contribute to disease progression in established SLI. A panel of biomarkers including G...

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Detalles Bibliográficos
Autores principales: Gremmels, Hendrik, Teraa, Martin, de Jager, Saskia C. A., Pasterkamp, Gerard, de Borst, Gert J., Verhaar, Marianne C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6656730/
https://www.ncbi.nlm.nih.gov/pubmed/31341203
http://dx.doi.org/10.1038/s41598-019-47217-1
Descripción
Sumario:Patients with Severe Limb Ischemia (SLI) have a high risk of amputation and mortality. Here, we investigated a panel of serum biomarkers with the aim of identifying biomarkers for major events and mechanisms that contribute to disease progression in established SLI. A panel of biomarkers including GROα, HGF, SCF, SCGFβ, SDF1α, TRAIL, IL-6, IL-8, FGFβ, GCSF, GMCSF, IP10, MCP1, PDGFbb, RANTES, TNFα, VEGF, sICAM, sVCAM, TM, and E-selectin was measured in serum samples from a subset (n = 108) of the JUVENTAS cohort. The primary outcome was major events, defined as major amputation or death. The inflammatory biomarkers IL-6, IL-8, GROα and IP-10 were significantly elevated in patients who reached a major endpoint. Results were validated in a secondary cohort (n = 146). Cox regression showed that adjusted hazard ratios were 1.40 (95% CI: 1.15–1.70, p = 0.0007) and 1.48 (95% CI 1.16–1.87, p = 0.001) for IL-6 and IP-10 in a fully adjusted model containing both biomarkers. A prediction model using IL-6 and IP-10 showed predictive accuracy with an AUC of ~ 78% in both discovery and validation cohorts, which is higher than previously published models. We conclude that inflammatory biomarkers predict major events in patients with SLI and allow the creation of biomarker-based risk-prediction models.