Division of Infection Medicine, Department of Clinical Sciences, Lund University, Lund, Sweden.
Division of Critical Care Medicine, Centre for Heart Lung Innovation, St. Paul's Hospital, University of British Columbia, Vancouver, BC, Canada.
PLoS One. 2020 Feb 20;15(2):e0229210. doi: 10.1371/journal.pone.0229210. eCollection 2020.
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.
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).
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.
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.
为了在急诊科（ED）尽早识别脓毒症患者，使用了各种风险分层评分和/或分诊系统。本研究的第一个目的是使用统计方法基于生命体征和生物标志物开发一种脓毒症风险分层评分。其次，我们旨在验证快速急诊分诊和治疗系统（RETTS）是否适用于脓毒症。RETTS 将生命体征与症状相结合进行风险分层。
我们回顾性分析了来自 ED 生物标志物研究的两项前瞻性、观察性、多中心队列患者的数据。使用最小绝对收缩和选择算子（LASSO）方法构建了一种名为基于肝素结合蛋白的脓毒症早期预警评分（SHEWS）的候选风险分层评分。SHEWS 和 RETTS 与国家早期预警评分 2（NEWS2）进行了比较，以评估感染相关器官功能障碍、72 小时内入住 ICU 或死亡（即脓毒症）的风险。
A 队列中，506 例确诊感染患者构成了 SHEWS 的推导队列和 RETTS 的验证队列。B 队列中有 435 例确诊感染患者，其中 184 例患者同时验证了这两个评分。在两个队列（A 和 B）中，NEWS2 对感染相关器官功能障碍、入住 ICU 或死亡的 AUC 均高于 RETTS，分别为 0.80（95%CI 0.76-0.84）和 0.69（95%CI 0.63-0.74），而 RETTS 分别为 0.74（95%CI 0.70-0.79）和 0.55（95%CI 0.49-0.60），p=0.05 和 p<0.01。在 B 队列中，SHEWS 的 AUC 最高，为 0.73（95%CI 0.68-0.79），p=0.32。
即使采用统计方法，我们也无法构建比 NEWS2 更好的脓毒症风险分层评分。RETTS 对脓毒症的筛查效果不如 NEWS2。
