Role of plasma TNF-α and IL-6 levels in prediction of acute respiratory distress syndrome based on their synchronous detection - GAN Zhixin; HE Binfeng; XU Jiancheng; WANG Guansong; XU Zhi (Di-san junyi daxue xuebao, 2020)
Objective To investigate the role of plasma TNF-α and IL-6 levels in prediction of occurrence of acute respiratory distress syndrome (ARDS) in high-risk patients. Methods A total of 30 patients who were at high risk for ARDS and enrolled in ICU of our Center of Respiratory and Critical Care Medicine from June 2018 to April 2019 were subjected in this study. Among them, 13 developed into ARDS (ARDS group), and the other 17 served as high risk group. Their clinical data and plasma samples at admission were collected. Plasma samples from 18 heath volunteers were also harvested. The soluble proteins, TNF-α and IL-6, in the samples were quantitatively detected by flow cytometry. Results The plasma levels of TNF-α and IL-6 were significantly higher in the ARDS patients than the high risk group and health control, while those in the high risk group also higher than those in the health control group (P < 0.05). The TNF-α level was closely associated with the progression of ARDS in high-risk patients. Furthermore, the patients of the ARDS group had significantly higher APACHE-Ⅱ score and higher levels of C-reactive protein, procalcitonin, direct bilirubin and lactic acid, while obviously lower oxygenation index and albumin level when compared with the high risk group (P < 0.05). Finally, from the 30 high risk patients, 15 died and 15 survived, and there were no notable differences in the TNF-α and IL-6 levels between the dead and survival (P>0.05). But the dead still had remarkably higher APACHE-Ⅱ score and levels of C-reactive protein, urea and uric acid, while obviously lower albumin, total plasma protein and oxygenation index than the survival (P < 0.05). Conclusion The plasma TNF-α level at admission is closely associated with the progression of ARDS in high-risk patients, and might be regarded as a marker to predict its occurrence.