Predictive performance of SOFA and qSOFA for in-hospital mortality in severe novel coronavirus disease

Am J Emerg Med. 2020 Oct;38(10):2074-2080. doi: 10.1016/j.ajem.2020.07.019. Epub 2020 Jul 12.

Abstract

Objectives: The assessment of illness severity at admission can contribute to decreased mortality in patients with the coronavirus disease (COVID-19). This study was conducted to evaluate the effectiveness of the Sequential Organ Failure Assessment (SOFA) and Quick Sequential Organ Failure Assessment (qSOFA) scoring systems at admission for the prediction of mortality risk in COVID-19 patients.

Methods: We included 140 critically ill COVID-19 patients. Data on demographics, clinical characteristics, and laboratory findings at admission were used to calculate SOFA and qSOFA against the in-hospital outcomes (survival or death) that were ascertained from the medical records. The predictive accuracy of both scoring systems was evaluated by the receiver operating characteristic (ROC) curve analysis.

Results: The area under the ROC curve for SOFA in predicting mortality was 0.890 (95% CI: 0.826-0.955), which was higher than that of qSOFA (0.742, 95% CI 0.657-0.816). An optimal cutoff of ≥3 for SOFA had sensitivity, specificity, positive predictive value, and negative predictive value of 90.00%, 83.18%, 50.00%, and 97.80%, respectively.

Conclusions: This novel report indicates that SOFA could function as an effective adjunctive risk-stratification tool at admission for critical COVID-19 patients. The performance of qSOFA is accepted but inferior to that of SOFA.

Keywords: Mortality; Novel coronavirus disease; Quick sequential organ failure assessment; Sequential organ failure assessment.

Publication types

  • Validation Study

MeSH terms

  • Age Factors
  • Aged
  • COVID-19 / mortality*
  • Comorbidity
  • Emergency Service, Hospital / statistics & numerical data
  • Female
  • Hospital Mortality
  • Humans
  • Male
  • Middle Aged
  • Organ Dysfunction Scores*
  • Pandemics
  • Predictive Value of Tests
  • ROC Curve
  • Retrospective Studies
  • SARS-CoV-2