Abstract

Background

The aim of this study was to investigate the relationship between baseline lymphocyte-monocyte ratio (LMR) and postoperative acute kidney injury (AKI) in patients with acute type A aortic dissection (ATAAD).

Methods

ATAAD patients undergoing surgery in Nanjing First Hospital were enrolled from January 2019 to April 2021. Lymphocyte and monocyte were measured on admission. Multivariable logistic regression analyses were performed to explore the relationship between LMR and postoperative AKI. We also used receiver operating characteristic (ROC), net reclassification index (NRI) and integrated discrimination improvement (IDI) analyses to assess the predictive ability of LMR.

Results

Among the 159 recruited patients, 47 (29.6%) were diagnosed with AKI. Univariate logistic regression analysis indicated that ATAAD patients with higher levels of LMR were prone to have lower risk to develop AKI (odds ratio [OR], 0.493; 95% confidence interval [CI] 0.284–0.650, P = 0.001). After adjustment for the potential confounders, LMR remained an independent related factor with postoperative AKI (OR 0.527; 95% CI 0.327–0.815, P = 0.006). The cutoff value for LMR to predict AKI was determined to be 2.67 in the ROC curve analysis (area under curve: 0.719). NRI and IDI further confirmed the predictive capability of LMR in postoperative AKI.

Conclusion

Elevated baseline LMR levels were independently associated with lower risk of postoperative AKI in ATAAD patients.

Details

Title
The association between lymphocyte-monocyte ratio and postoperative acute kidney injury in patients with acute type A aortic dissection
Author
Chen, Wenxiu; Song, Xiaochun; Liang, Hong; Xu, Huan; Qian, Yan; Zhang, Wenhao; Sun, Jiakui; Shen, Xiao; Liu, Ying; Wang, Xiang; Shi, Qiankun; Liu, Han; Mu, Xinwei; Zhang, Cui
Pages
1-8
Section
Research article
Publication year
2022
Publication date
2022
Publisher
BioMed Central
e-ISSN
1749-8090
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2651969594
Copyright
© 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.