Predictive Performance of Quick Sequential Organ Failure Assessment Scoring in an Argentinian Hospital
Journal Title: Journal of Clinical and Diagnostic Research - Year 2018, Vol 12, Issue 10
Abstract
ABSTRACT Introduction: The early identification and treatment of sepsis in emergency setting could improve patients’ survival. The Quick-SOFA score is a simple tool that could contribute to this identification. Aim: To evaluate mortality rate in Emergency Department along with predicting sepsis by Quick-SOFA. Materials and Methods: This was an observational, prospective study performed in an emergency department of an Argentine Hospital. The studied patients were ≥18 years of age, with infection or suspicion of infection. For qSOFA, 1 point was assigned for each of following: respiratory rate >21 breaths/min, systolic arterial blood pressure ≤100 mm Hg, and altered mental status. A qSOFA score of ≥2 was considered positive. To assess the performances of the qSOFA and SIRS, sensitivity and specificity was calculated. Results: A total of 157 patients were included with mean age corresponding to 62.9±19.2 years out of which 76 (48.4%) patients were women. Upon admission, 58/157 (36.9%) patients showed a positive-qSOFA, and 120/157 (76.4%) patients were SIRS positive (≥2 signs). 69/157 (46%) cases developed sepsis; 22/157(14%) patients died during their stay. The discrimination of sepsis using qSOFA was comparable with the SIRS criteria (p=0.399) and the discrimination of in-hospital mortality using qSOFA was better than SIRS criteria (p=0.0488). A qSOFA Area Under the Curve (AUC) for predicting sepsis was 0.765 (95% CI 0.69-0.84) while qSOFA AUC for predicting in-hospital mortality was 0.71, (95% CI 0.59-0.83). Conclusion: The newly introduced qSOFA provided better discrimination than SIRS for predicting in-hospital mortality whereas both scores showed comparable discrimination for predicting sepsis in Emergency Department.
Authors and Affiliations
Javier Osatnik, Bárbara Tort-Oribea, Juan Folco, Ariel Sosa, Dabiel Ivulich, María Mercedes Kleinert, Javier Eugenio Roberti
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