医学
败血症
沙发评分
预警得分
接收机工作特性
内科学
全身炎症反应综合征
危险系数
器官功能障碍
急诊医学
置信区间
作者
Tamás Szakmány,Richard Pugh,Maja Kopczynska,Robert M. Lundin,Ben Sharif,P. Morgan,G Ellis,J. Abreu,Svetlana Kulikouskaya,Khalid Bashir,Lauren J. Galloway,Hassan H. Alhassan,Thomas Grother,Paul McNulty,Steffan Seal,Alice Cains,M. Vreugdenhil,Mustafa Abdimalik,Naomi Dennehey,Gerry Evans
出处
期刊:Anaesthesia
[Wiley]
日期:2017-11-17
卷期号:73 (2): 195-204
被引量:56
摘要
Summary Our aim was to prospectively determine the predictive capabilities of SEPSIS ‐1 and SEPSIS ‐3 definitions in the emergency departments and general wards. Patients with National Early Warning Score (NEWS) of 3 or above and suspected or proven infection were enrolled over a 24‐h period in 13 Welsh hospitals. The primary outcome measure was mortality within 30 days. Out of the 5422 patients screened, 431 fulfilled inclusion criteria and 380 (88%) were recruited. Using the SEPSIS ‐1 definition, 212 patients had sepsis. When using the SEPSIS ‐3 definitions with Sequential Organ Failure Assessment (SOFA) score ≥ 2, there were 272 septic patients, whereas with quick SOFA score ≥ 2, 50 patients were identified. For the prediction of primary outcome, SEPSIS ‐1 criteria had a sensitivity (95%CI) of 65% (54–75%) and specificity of 47% (41–53%); SEPSIS ‐3 criteria had a sensitivity of 86% (76–92%) and specificity of 32% (27–38%). SEPSIS ‐3 and SEPSIS ‐1 definitions were associated with a hazard ratio (95%CI) 2.7 (1.5–5.6) and 1.6 (1.3–2.5), respectively. Scoring system discrimination evaluated by receiver operating characteristic curves was highest for Sequential Organ Failure Assessment score (0.69 (95%CI 0.63–0.76)), followed by NEWS (0.58 (0.51–0.66)) (p < 0.001). Systemic inflammatory response syndrome criteria (0.55 (0.49–0.61)) and quick SOFA score (0.56 (0.49–0.64)) could not predict outcome. The SEPSIS ‐3 definition identified patients with the highest risk. Sequential Organ Failure Assessment score and NEWS were better predictors of poor outcome. The Sequential Organ Failure Assessment score appeared to be the best tool for identifying patients with high risk of death and sepsis‐induced organ dysfunction.
科研通智能强力驱动
Strongly Powered by AbleSci AI