Background: The prognostic value of quick sepsis-related organ failure assessment (qSOFA) outside intensive care units has been criticized. Therefore, we aimed to improve its ability in predicting 30-day all-cause mortality, and in ruling out the cases at high risk of death among patients with suspected or confirmed sepsis at emergency department (ED) admission. Methods: This study is a secondary analysis of a prospective multicenter study. We built three predictive models combining qSOFA with the clinical variables and serum biomarkers that resulted in an independent association with 30-day mortality, in both 848 undifferentiated patients (Group 1) and in 545 patients definitively diagnosed with sepsis (Group 2). The models reaching the highest negative predictive value (NPV) with the minimum expenditure of biomarkers in Group 1 and in Group 2 were validated in two cohorts of patients initially held out due to missing data. Results: In terms of the area under the receiver-operating characteristic curve, all six models significantly exceeded qSOFA in predicting prognosis. An "extended" qSOFA (eqSOFA1) in Group 1 and an eqSOFA2 integrated with C-reactive protein and mid-regional proadrenomedullin (eqSOFA2+CRP+MR-proADM) in Group 2 reached the best NPV (0.94 and 0.93, respectively) and ease of use. eqSOFA1 and eqSOFA2+CRP+MR-proADM performed equally well in both the inception and validation cohorts. Conclusions: We have derived and validated two prognostic models that outweigh qSOFA in predicting mortality and in identifying the low risk of death among patients with suspected or confirmed sepsis at ED admission.

The Integration of qSOFA with Clinical Variables and Serum Biomarkers Improves the Prognostic Value of qSOFA Alone in Patients with Suspected or Confirmed Sepsis at ED Admission

Barbati, Giulia;Lupia, Enrico;
2020-01-01

Abstract

Background: The prognostic value of quick sepsis-related organ failure assessment (qSOFA) outside intensive care units has been criticized. Therefore, we aimed to improve its ability in predicting 30-day all-cause mortality, and in ruling out the cases at high risk of death among patients with suspected or confirmed sepsis at emergency department (ED) admission. Methods: This study is a secondary analysis of a prospective multicenter study. We built three predictive models combining qSOFA with the clinical variables and serum biomarkers that resulted in an independent association with 30-day mortality, in both 848 undifferentiated patients (Group 1) and in 545 patients definitively diagnosed with sepsis (Group 2). The models reaching the highest negative predictive value (NPV) with the minimum expenditure of biomarkers in Group 1 and in Group 2 were validated in two cohorts of patients initially held out due to missing data. Results: In terms of the area under the receiver-operating characteristic curve, all six models significantly exceeded qSOFA in predicting prognosis. An "extended" qSOFA (eqSOFA1) in Group 1 and an eqSOFA2 integrated with C-reactive protein and mid-regional proadrenomedullin (eqSOFA2+CRP+MR-proADM) in Group 2 reached the best NPV (0.94 and 0.93, respectively) and ease of use. eqSOFA1 and eqSOFA2+CRP+MR-proADM performed equally well in both the inception and validation cohorts. Conclusions: We have derived and validated two prognostic models that outweigh qSOFA in predicting mortality and in identifying the low risk of death among patients with suspected or confirmed sepsis at ED admission.
2020
9
4
1205
1218
C-reactive protein; and soluble IL-2 receptor α; biomarkers; lactate; mid-regional proadrenomedullin; presepsin; procalcitonin; sepsis; soluble triggering receptor expressed on myeloid cell-1; soluble tumor necrosis factor receptor-1
Mearelli, Filippo; Barbati, Giulia; Casarsa, Chiara; Giansante, Carlo; Breglia, Andrea; Spica, Andrea; Moras, Cristina; Olivieri, Gaia; Occhipinti, Alessandro Agostino; De Nardo, Margherita; Spagnol, Francesca; Fiotti, Nicola; Di Girolamo, Filippo Giorgio; Ruscio, Maurizio; Castello, Luigi Mario; Colonetti, Efrem; Marino, Rossella; Ronco, Claudio; Zanetti, Michela; Lupia, Enrico; Muiesan, Maria Lorenza; Di Somma, Salvatore; Avanzi, Gian Carlo; Biolo, Gianni
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1742461
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