Systemic inflammatory response syndrome-based severe sepsis screening algorithms in emergency department patients with suspected sepsis

Abstract

Objective: Systemic inflammatory response syndrome (SIRS)-based severe sepsis screening algorithms have been utilised in stratification and initiation of early broad spectrum antibiotics for patients presenting to EDs with suspected sepsis. We aimed to investigate the performance of some of these algorithms on a cohort of suspected sepsis patients.

Methods: We conducted a retrospective analysis on an ED-based prospective sepsis registry at a tertiary Sydney hospital, Australia. Definitions for sepsis were based on the 2012 Surviving Sepsis Campaign guidelines. Numerical values for SIRS criteria and ED investigation results were recorded at the trigger of sepsis pathway on the registry. Performance of specific SIRS-based screening algorithms at sites from USA, Canada, UK, Australia and Ireland health institutions were investigated.

Results: Severe sepsis screening algorithms' performance was measured on 747 patients presenting with suspected sepsis (401 with severe sepsis, prevalence 53.7%). Sensitivity and specificity of algorithms to flag severe sepsis ranged from 20.2% (95% CI 16.4-24.5%) to 82.3% (95% CI 78.2-85.9%) and 57.8% (95% CI 52.4-63.1%) to 94.8% (95% CI 91.9-96.9%), respectively. Variations in SIRS values between uncomplicated and severe sepsis cohorts were only minor, except a higher mean lactate (>1.6 mmol/L, P < 0.01).

Conclusions: We found the Ireland and JFK Medical Center sepsis algorithms performed modestly in stratifying suspected sepsis patients into high-risk groups. Algorithms with lactate levels thresholds of >2 mmol/L rather than >4 mmol/L performed better. ED sepsis registry-based characterisation of patients may help further refine sepsis definitions of the future.

Keywords: algorithm; anti-bacterial agent; sensitivity and specificity; severe sepsis; systemic inflammatory response syndrome.