The Validity of Neutrophil/lymphocyte Ratio as A Predictive Factor for Systemic Inflammatory Response Syndrome after Flexible Ureteroscopy Lithotripsy
Urology Journal,
Vol. 19 No. 01 (2022),
18 Esfand 2022
,
Page 17-21
https://doi.org/10.22037/uj.v19i01.6570
Abstract
Purpose: To explore the risk factors and predictive factors of systemic inflammatory response syndrome (SIRS) after flexible ureteroscopy (fURS) for upper urinary tract stones.
Materials and Methods: Patients who underwent fURS from January 2014 to September 2019 were retrospectively analyzed, which were divided into the SIRS group and non-SIRS group. Clinical data of all patients, including gender, age, American society of anesthesia score, diabetes, etc., were collected. Univariate and multivariate logistic regression was used to determine the independent risk factors for SIRS after fURS, and the receiver operating characteristic (ROC) curve was drawn to verify the validity of the results. In addition, patients from October 2019 to January 2020 were prospectively collected to verify the results.
Results: A total of 369 patients were retrospectively included. Univariate analysis showed significant differences in postoperative stone residuals (P = 0.039), preoperative neutrophil/ lymphocyte ratio (NLR) (P < 0.001), and lymphocyte/monocyte ratio (LMR) (P = 0.001) between two groups. Further, preoperative NLR and postoperative stone residuals were independent according to multivariate logistic regression analysis. The optimal cut-off value of preoperative NLR by ROC curve was 2.61, and the area under ROC curve was 77.9%. Prospective analysis based on 53 patients showed that the incidence of SIRS in patients with NLR > 2.61 was significantly higher than that in other patients. (RR = 4.932, P = 0.040).
Conclusion: Preoperative NLR can be used as a predictive factor for SIRS in patients with fURS according to our study. It may provide an evidence for clinicians to make preoperative decisions or medical plans.
- FUSL, SIRS, Neutrophil / lymphocyte ratio, logistic analysis
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