A novel infrared spectroscopy marker for assessing the postoperative infection risk in patients with upper urinary tract calculus

Abstract

Abstract The aim of this study is to evaluate the ability of infrared wavenumber of calculus to predict postoperative infection in patients with upper urinary tract calculus (UUTC), and to establish a predictive model based on this. From March 2018 to March 2023, 480 UUTC patients from Fujian Provincial Hospital were included in this study. The infrared-wavenumbers related infection score (IR-infection score) was constructed by univariate analysis, multicollinearity screening, and Lasso analysis to predict postoperative infection. Continually, the Delong test was used to compare the predictive power between the IR-infection score and traditional indicators. Afterward, we performed urine metagene sequencing and stone culture to prove the correlation between calculus toxicity and IR-infection score. Finally, logistic regression was used to build a nomogram. IR-infection score composed of four independent wavenumbers could precisely predict postoperative infection (AUCvalidation cohort = 0.707) and sepsis (AUCvalidation cohort = 0.824). IR-infection score had better predictive ability than commonly used clinical indicators. Moreover, metagenomics sequencing and calculus culture confirmed the correlation between IR-infection score and calculus toxicity (all P 0.803). Our study first developed a novel infrared spectroscopy marker and nomogram, which can help urologists better predict postoperative infection in UUTC patients.

Keywords

• Upper urinary tract calculus
• Postoperative infection
• Infrared spectrum
• Calculus toxicity