Risk prediction of biomarkers for early multiple organ dysfunction in critically ill patients

医学 降钙素原 器官功能障碍 重症监护室 生物标志物 多器官功能障碍综合征 内科学 急诊科 全身炎症反应综合征 沙发评分 疾病严重程度 置信区间 阿帕奇II 观察研究 曲线下面积 败血症 化学 精神科 生物化学
作者
Shigeto Ishikawa,Yuto Teshima,Hiroki Otsubo,Takashi Shimazui,Taka‐aki Nakada,Osamu Takasu,Kazuo Matsuda,Junichi Sasaki,Masakazu Nabeta,Takeshi Moriguchi,Takayuki Shibusawa,Toshihiko Mayumi,Shigeto Oda
出处
期刊:BMC Emergency Medicine [BioMed Central]
卷期号:21 (1) 被引量:4
标识
DOI:10.1186/s12873-021-00534-z
摘要

Shock and organ damage occur in critically ill patients in the emergency department because of biological responses to invasion, and cytokines play an important role in their development. It is important to predict early multiple organ dysfunction (MOD) because it is useful in predicting patient outcomes and selecting treatment strategies. This study examined the accuracy of biomarkers, including interleukin (IL)-6, in predicting early MOD in critically ill patients compared with that of quick sequential organ failure assessment (qSOFA).This was a multicenter observational sub-study. Five universities from 2016 to 2018. Data of adult patients with systemic inflammatory response syndrome who presented to the emergency department or were admitted to the intensive care unit were prospectively evaluated. qSOFA score and each biomarker (IL-6, IL-8, IL-10, tumor necrosis factor-α, C-reactive protein, and procalcitonin [PCT]) level were assessed on Days 0, 1, and 2. The primary outcome was set as MOD on Day 2, and the area under the curve (AUC) was analyzed to evaluate qSOFA scores and biomarker levels.Of 199 patients, 38 were excluded and 161 were included. Patients with MOD on Day 2 had significantly higher qSOFA, SOFA, and Acute Physiology and Chronic Health Evaluation II scores and a trend toward worse prognosis, including mortality. The AUC for qSOFA score (Day 0) that predicted MOD (Day 2) was 0.728 (95% confidence interval [CI]: 0.651-0.794). IL-6 (Day 1) showed the highest AUC among all biomarkers (0.790 [95% CI: 0.711-852]). The combination of qSOFA (Day 0) and IL-6 (Day 1) showed improved prediction accuracy (0.842 [95% CI: 0.771-0.893]). The combination model using qSOFA (Day 1) and IL-6 (Day 1) also showed a higher AUC (0.868 [95% CI: 0.799-0.915]). The combination model of IL-8 and PCT also showed a significant improvement in AUC.The addition of IL-6, IL-8 and PCT to qSOFA scores improved the accuracy of early MOD prediction.

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