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Published on: October 20, 2012
The Predictive Value of Systemic Inflammatory Biomarkers in Predicting Postoperative Systemic Inflammatory Response
Qi Wei1,2, AiMin Liu2, ZhiYong Sun2
1Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Medical University and Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, People's Republic of China.
Purpose:
The aim of the study was to evaluate the predictive significance of several systemic inflammatory biomarkers, namely neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR) and systemic immune inflammatory index (SII) in relation to the occurrence of systemic inflammatory response syndrome (SIRS) after percutaneous nephrolithotomy (PCNL).
Methods:
A cohort of 317 patients who underwent PCNL were retrospectively recruited and evaluated. Based on the subsequent occurrence of SIRS after PCNL, patients were divided into two different groups: SIRS (n = 51) and non-SIRS (n = 266). We examined the effect of neutrophil-to-lymphocyte ratio(NLR), lymphocyte-to-monocyte ratio(LMR), platelet-to-lymphocyte ratio(PLR), and systemic immunoinflammatory index (SII), as well as other demographic characteristics and surgical factors to predict the development of SIRS. Univariate analysis and multivariate logistic regression were used to identify independent predictors of SIRS after PCNL. In addition, receiver operating characteristic (ROC) curves were constructed and area under the curve (AUC) values were calculated to evaluate and compare the discriminatory ability of the studied systemic inflammatory biomarkers.
Results:
The NLR, PLR, and SII values in the SIRS group were significantly increased compared to those in the non-SIRS group. Multivariate analysis revealed NLR (OR = 1.292, 95% CI: 1.047-1.594, P = 0.017), PLR (OR = 1.008, 95% CI: 1.001-1.016, P = 0.032) and SII (OR = 1.001, 95%CI: 1.000-1.003, P = 0.016) as independent predictors of SIRS development after PCNL. Furthermore, ROC curve analysis highlighted the discriminative ability of NLR, PLR and SII with AUC values of 0.638, 0.644 and 0.680, respectively.
Conclusion:
These results highlight the importance of preoperative NLR, PLR and SII as reliable indicators for risk prediction of SIRS after PCNL. In response to these findings, it is critical to perform careful and comprehensive preoperative evaluations of these patients while developing tailored treatment strategies.
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