Dynamic changes in serum IL-6, IL-8, and IL-10 predict the outcome of ICU patients with severe COVID-19
Author(s) -
Jia Li,
Rong Liu,
Ran Cui,
Jiaqi Feng,
Yuyang Jin,
Xiaoxiang Chen,
Renying Xu
Publication year - 2021
Publication title -
annals of palliative medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.546
H-Index - 19
eISSN - 2224-5839
pISSN - 2224-5820
DOI - 10.21037/apm-20-2134
Subject(s) - medicine , intensive care unit , tocilizumab , biomarker , covid-19 , interleukin , severity of illness , interleukin 6 , disease , gastroenterology , cytokine , biochemistry , chemistry , infectious disease (medical specialty)
BACKGROUNDBiomarkers to prognosticate the outcomes and guide the treatment of patients with severe coronavirus disease 2019 (COVID-19) are currently required. We aimed to investigate whether the dynamic variation of cytokines was associated with the survival of patients admitted to the intensive care unit (ICU).METHODSA retrospective study was performed on 40 patients with COVID-19 admitted to the ICU in Wuhan, China. Demographic, clinical, and laboratory variables were collected, and serum cytokines were kinetically assessed. A multivariable-adjusted generalized linear regression model was used to analyze the differences in serum cytokine levels between survivors and non-survivors.RESULTSAmong the 40 patients included, we found a positive correlation between multiple cytokines. Serum levels of interleukin (IL)-6, IL-10, and tumor necrosis factor alpha (TNFα) in non-survivors were consistently elevated compared to those in the survivors. Kinetic variations in IL-6, IL-8, and IL-10 were associated with a fatal outcome in patients with severe COVID-19, independent of sex, age, absolute lymphocyte count, direct bilirubin, hypertension, chronic obstructive pulmonary disease, and cancer as well as the use of glucocorticoids and tocilizumab.CONCLUSIONSDynamic changes in serum IL-6, IL-8, and IL-10 levels were associated with survival in patients in the ICU, and could serve as a predictive biomarker to determine the therapeutic options for patients with severe COVID-19.
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