NEWS, SIRS and qSOFA criteria for predicting sepsis and sepsis with high risk of death in emergency room: A comparison study and improved predictive models based on local data from CETAT and MIMIC-IV databases

Abstract

Early identification of sepsis in emergency room patients is critical for initiating timely interventions, highlighting the need for effective predictive scoring systems. A retrospective observational study was conducted using data from the CETAT database collected between December 2019 and October 2021. The study evaluated how well the SIRS, qSOFA, and NEWS scoring systems, along with logistic regression models, predict sepsis and high-risk sepsis in emergency room patients. The logistic regression models were further optimized by incorporating additional features based on local data.A total of 12,799 patients were analyzed, including 1,360 sepsis cases, of which 373 were classified as high-risk sepsis. The NEWS score demonstrated superior predictive performance compared to qSOFA and SIRS, with an AUC-ROC of 0.737 (95% CI 0.72–0.75) for sepsis and 0.653 (95% CI 0.62–0.69) for high-risk sepsis. After optimization, the NEWS-based model improved to an AUC-ROC of 0.756 (95% CI 0.74–0.77) for sepsis and 0.718 (95% CI 0.69–0.75) for high-risk sepsis. Further enhancement was observed with the inclusion of additional clinical variables, resulting in AUC-ROC values of 0.834 (95% CI 0.82–0.85) for sepsis and 0.756 (95% CI 0.73–0.78) for high-risk sepsis. Data from the MIMIC-IV database, which included sepsis status and relevant variables for SIRS, qSOFA, and NEWS score calculations, confirmed that the optimized NEWS-based model improved the sepsis prediction AUC-ROC from 0.690 (95% CI 0.68–0.70) to 0.708 (95% CI 0.70–0.72), and consistently outperformed qSOFA and SIRS in sepsis prediction.

Keywords

• sepsis
• emergency room
• CETAT
• MIMIC-IV
• scoring system