RESUMO
BACKGROUND: The inability to identify individuals with acute fever at risk of death is a barrier to effective triage and management of severe infections, especially in low-resource settings. Since endothelial and immune activation contribute to the pathogenesis of various distinct life-threatening infections, we hypothesized that measuring mediators of these pathways at clinical presentation would identify febrile adults at risk of death. METHODS: Plasma concentrations of markers of endothelial (angiopoetin-1/2, soluble fms-like tyrosine kinase-1, soluble vascular cell adhesion molecule-1, soluble intercellular adhesion molecule-1) and immune (soluble triggering receptor expressed on myeloid cells [sTREM-1], interleukin-6, interleukin-8, chitinase-3-like protein-1, soluble tumor necrosis factor receptor-1, procalcitonin [PCT], C-reactive protein [CRP]) activation pathways were determined in consecutive adults with acute fever (≥38°C) at presentation to outpatient clinics in Dar es Salaam, Tanzania. We evaluated the accuracy of these mediators in predicting all-cause mortality and examined whether markers could improve the prognostic accuracy of clinical scoring systems, including the quick sequential organ failure assessment (qSOFA) and Glasgow coma scale (GCS). RESULTS: Of 507 febrile adults, 32 died (6.3%) within 28 days of presentation. We found that sTREM-1 was the best prognostic marker for 28-day mortality (area under the receiver operating characteristic [AUROC] 0.87, 95% confidence interval [CI] 0.81-0.92) and was significantly better than CRP (P < .0001) and PCT (P = .0001). The prognostic accuracy of qSOFA and the GCS were significantly enhanced when sTREM-1 was added (0.80 [95% CI 0.76-0.83] to 0.91 [95% CI 0.88-0.94; P < .05] and 0.72 [95% CI 0.63-0.80] to 0.94 [95% CI 0.91-0.97; P < .05], respectively). CONCLUSIONS: Measuring sTREM-1 at clinical presentation can identify febrile individuals at risk of all-cause febrile mortality. Adding severity markers such as sTREM-1 to simple clinical scores could improve the recognition and triage of patients with life-threatening infections in resource-limited settings.
