Scores for sepsis detection and risk stratification - construction of a novel score using a statistical approach and validation of RETTS

PLoS One. 2020 Feb 20;15(2):e0229210. doi: 10.1371/journal.pone.0229210. eCollection 2020.

Abstract

Background: To allow early identification of patients at risk of sepsis in the emergency department (ED), a variety of risk stratification scores and/or triage systems are used. The first aim of this study was to develop a risk stratification score for sepsis based upon vital signs and biomarkers using a statistical approach. Second, we aimed to validate the Rapid Emergency Triage and Treatment System (RETTS) for sepsis. RETTS combines vital signs with symptoms for risk stratification.

Methods: We retrospectively analysed data from two prospective, observational, multicentre cohorts of patients from studies of biomarkers in ED. A candidate risk stratification score called Sepsis Heparin-binding protein-based Early Warning Score (SHEWS) was constructed using the Least Absolute Shrinkage and Selector Operator (LASSO) method. SHEWS and RETTS were compared to National Early Warning Score 2 (NEWS2) for infection-related organ dysfunction, intensive care or death within the first 72h after admission (i.e. sepsis).

Results: 506 patients with a diagnosed infection constituted cohort A, in which SHEWS was derived and RETTS was validated. 435 patients constituted cohort B of whom 184 had a diagnosed infection where both scores were validated. In both cohorts (A and B), AUC for infection-related organ dysfunction, intensive care or death was higher for NEWS2, 0.80 (95% CI 0.76-0.84) and 0.69 (95% CI 0.63-0.74), than RETTS, 0.74 (95% CI 0.70-0.79) and 0.55 (95% CI 0.49-0.60), p = 0.05 and p <0.01, respectively. SHEWS had the highest AUC, 0.73 (95% CI 0.68-0.79) p = 0.32 in cohort B.

Conclusions: Even with a statistical approach, we could not construct better risk stratification scores for sepsis than NEWS2. RETTS was inferior to NEWS2 for screening for sepsis.

Publication types

  • Multicenter Study
  • Observational Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Emergency Service, Hospital / statistics & numerical data*
  • Emergency Treatment / statistics & numerical data*
  • Female
  • Follow-Up Studies
  • Hospital Mortality / trends*
  • Hospitalization / statistics & numerical data
  • Humans
  • Male
  • Middle Aged
  • Models, Statistical*
  • Predictive Value of Tests
  • Prospective Studies
  • ROC Curve
  • Retrospective Studies
  • Risk Assessment / methods*
  • Sepsis / diagnosis*
  • Triage / standards*

Grants and funding

Swedish Government Funds for Clinical Research (ALF), the Crafoord foundation, the Swedish Society of Medicine, the Thelma Zoégas foundation, the foundation of Apotekare Hedberg, the foundation of Magnus Bergvall, the Royal Physiographic Society, Lund, the Foundations of Skåne University Hospital, the foundation of Alfred Österlund and, the foundation of Clas Groschinsky The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.