A Prospective Study of the Association of IL6 with the Critical Unit and Their Effect on in-Hospital Mortality in Critically Ill Patients

IL6 与重症病房的关联及其对危重患者住院死亡率影响的前瞻性研究

阅读:4
作者:Guangjian Wang #, Hui Lian #, Qirui Guo, Hongmin Zhang, Xiaoting Wang

Conclusion

Our study innovatively integrated mitochondrial and endothelial markers in the critical unit to comprehensively evaluate patient prognosis, which may be a trend in the future assessment of critically ill patients. There are few such studies, and ours may promote the progress of related research.

Methods

This study included adult patients admitted to the intensive care unit for various reasons from January 1st to May 31st, 2023. Baseline characteristics, intensive care unit parameters, and laboratory test and outcome data were obtained from the electronic medical records system. Critical unit parameters were measured using polymerase chain reaction and enzyme-linked immunosorbent assay methods. Correlations were examined between IL6, critical unit parameters, and various outcomes.

Purpose

We previously proposed a new concept, the "critical unit", which covers the structural integrity and function of mitochondria and endothelium. Injury of the critical unit plays a key role in the development of critical illnesses. High levels of inflammation may lead to abnormalities of the critical unit, which is an important mechanism for critical illnesses, and both inflammation and critical unit dysfunction may affect patient prognosis. Here we evaluated the correlation between interleukin-6 (IL6) and the critical unit biomarkers in critically ill patients and the impact of both on prognosis. Patients and

Results

In critically ill patients, IL6 was closely associated with all the critical unit biomarkers (activated partial thromboplastin time, sphingosine 1-phosphate, mitochondrial DNA, mitochondrial fission 1, and Parkin) and the prognoses of patients. A nomogram was constructed using the critical unit biomarkers to predict the in-hospital mortality of critically ill patients. The area under the curve for the mortality prediction model was 0.708. In sensitivity analyses, the predictive effect was better in the non-surgery and tumor groups compared with the surgery and non-tumor groups, with area under the curve values of 0.885 and 0.891, respectively.

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。