Relation between macrophage inflammatory protein-1 and intercellular adhesion molecule-1 and computed tomography findings in critically-ill saudi covid-19 patients

巨噬细胞炎症蛋白-1和细胞间黏附分子-1与沙特阿拉伯重症新冠肺炎患者计算机断层扫描结果的关系

阅读:1

Abstract

BACKGROUND: Several, clinical and biochemical factors were suggested as risk factors for more severe forms of Covid-19. Macrophage inflammatory protein-1 alpha (MIP-1α, CCL3) is a chemokine mainly involved in cell adhesion and migration. Intracellular adhesion molecule 1 (ICAM-1) is an inducible cell adhesion molecule involved in multiple immune processes. The present study aimed to assess the relationship between baseline serum MIP-1α and ICAM-1 level in critically-ill Covid-19 patients and the severity of computed tomography (CT) findings. METHODS: The study included 100 consecutive critically-ill patients with Covid-19 infection. Diagnosis of infection was established on the basis of RT-PCR tests. Serum MIP-1α and ICAM-1 levels were assessed using commercially available ELISA kits. All patients were subjected to a high-resolution computed tomography assessment. RESULTS: According to the computed tomography severity score, patients were classified into those with moderate/severe (n=49) and mild (n = 51) pulmonary involvement. Severe involvement was associated with significantly higher MIP-1α and ICAM-1 level. Correlation analysis identified significant positive correlations between MIP-1α and age, D-dimer, IL6, in contrast, there was an inverse correlation with INF-alpha. Additionally, ICAM-1 showed significant positive correlations with age, D-Dimer,- TNF-α, IL6,while an inverse correlation with INF-alpha was observed. CONCLUSIONS: MIP-1α and ICAM-1 level are related to CT radiological severity in Covid-19 patients. Moreover, these markers are well-correlated with other inflammatory markers suggesting that they can be used as reliable prognostic markers in Covid-19 patients.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。