Predicting mortality in patients with systemic inflammatory response syndrome: an evaluation of two prognostic models, two soluble receptors, and a macrophage migration inhibitory factor.

摘要

Better outcomes in patients suspected of community-acquired infections requires the optimal and timely assessment of disease severity at the point of first contact with the health care system, which is typically in the emergency department. This study was conducted using a previously described, prospectively collected cohort of patients with systemic inflammatory response syndrome (SIRS) that were admitted to an emergency department and a department of infectious diseases at a university hospital. Plasma samples were collected and disease severity scores calculated upon admission. A multiplex immunoassay and a newly developed enzyme-linked immunosorbent assay (ELISA)-based assay were used to measure the soluble urokinase-type plasminogen activator receptor, soluble triggering receptor expressed on myeloid cells-1, and macrophage migration inhibitory factor. The area under the receiver operating characteristic (ROC) curve for the prediction of 30- and 180-day mortality was used to compare the performance of the markers and the models. A total of 151 patients were eligible for analysis. Of these, nine died before day 30 and 19 died before day 180 post-admission. Admission-soluble urokinase-type plasminogen activator receptor levels were significantly higher in both day 30 and day 180 non-survivors. There was a non-significant trend towards higher macrophage migration inhibitory factor concentrations in day 30 non-survivors. Soluble triggering receptor expressed on myeloid cells-1 levels were significantly lower in non-survivors at both time points. The simplified acute physiology score II (SAPS II) and sequential organ failure assessment (SOFA) scores were significantly higher in non-survivors at both time points, indicating that these models intended for use in intensive care units might also be useful in an emergency department setting.