Blood Interleukin-6 Levels Predict Multiple Organ Dysfunction in Critically Ill Patients. Issue 6 (June 2021)

• Record Type: Journal Article
• Authors: Shimazui, Takashi; Nakada, Taka-aki; Yazaki, Megumi; Mayumi, Toshihiko; Takasu, Osamu; Matsuda, Kenichi; Sasaki, Junichi; Otsubo, Hiroki; Teshima, Yuto; Nabeta, Masakazu; Moriguchi, Takeshi; Shibusawa, Takayuki; Oda, Shigeto
• Is Part Of: Shock. Volume 55:Issue 6(2021)
• Publication Date: 2021-06
• Subjects: Biomarker -- critically ill -- cytokine storm -- organ dysfunction -- predictive marker -- predictive value -- APACHE II -- Acute Physiology and Chronic Health Evaluation II -- AUC -- area under the receiver operating characteristic curve -- CRP -- C-reactive protein -- DAMPs -- damage-associated molecular patterns -- Denver -- Denver multiple organ failure -- ED -- emergency department -- ICU -- intensive care unit -- IL -- interleukin -- MOD -- multiple organ dysfunction -- MODS -- Marshall multiple organ dysfunction -- MOF -- multiple organ failure -- PAMPs -- pathogen-associated molecular patterns -- PCT -- procalcitonin -- ROC -- receiver operating characteristic -- SIRS -- systemic inflammatory response syndrome -- SOFA -- sequential organ failure assessment -- TNF-α -- tumor-necrosis factor-α -- WBC -- White blood cell; Shock -- Periodicals; Shock -- Periodicals; Choc (Pathologie) -- Périodiques; Shock; Periodicals; 616.0475
• DOI: 10.1097/SHK.0000000000001678
• Languages: English
• ISSNs: 1073-2322

Abstract

ABSTRACT: Background: Predicting multiple organ dysfunction (MOD) in the late phase of critical illnesses is essential. Cytokines are considered biomarkers that can predict clinical outcomes; however, their predictive value for late-phase MOD is unknown. This study aimed to identify the biomarker with the highest predictive value for late-phase MOD. Methods: This observational study prospectively evaluated data on adult patients with systemic inflammatory response syndrome, those who presented to the emergency department or were admitted to intensive care units in five tertiary hospitals (n = 174). Seven blood biomarkers levels (interleukin-6 [IL-6], IL-8, IL-10, tumor-necrosis factor-α, white blood cells, C-reactive protein, and procalcitonin) were measured at three timepoints (days 0, 1, and 2). The area under the receiver operating characteristic curve (AUC) was analyzed to evaluate predictive values for MOD (primary outcome, MOD on day 7 [late-phase]; secondary outcome, MOD on day 3 [early-phase]). Results: Of the measured 7 biomarkers, blood IL-6 levels on day 2 had the highest predictive value for MOD on day 7 using single timepoint data (AUC 0.825, 95% confidence interval [CI] 0.754–0.879). Using three timepoint biomarkers, blood IL-6 levels had the highest predictive value of MOD on day 7 (AUC 0.838, 95% CI 0.768–0.890). Blood IL-6 levels using three timepoint biomarkers had also the highest predictive value for MOD on day 3 (AUC 0.836, 95% CI 0.766–0.888). Conclusion: Of the measured biomarkers, blood IL-6 levels had the highest predictive value for MOD on days 3 and 7. Blood IL-6 levels predict early- and late-phase MOD in critically ill patients. Abstract : Supplemental Digital Content is available in the text