The Shengli Clinical Medical College, Fujian Medical University, Fuzhou, 350001, Fujian, China.
Department of Urology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, 350001, Fujian, China.
Sci Rep. 2024 Aug 21;14(1):19398. doi: 10.1038/s41598-024-69720-w.
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 (AUC = 0.707) and sepsis (AUC = 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 < 0.05). The nomogram based on the IR-infection score had high predictive power (all AUCs > 0.803). Our study first developed a novel infrared spectroscopy marker and nomogram, which can help urologists better predict postoperative infection in UUTC patients.
本研究旨在评估结石红外波数预测上尿路结石（UUTC）患者术后感染的能力，并在此基础上建立预测模型。 2018 年 3 月至 2023 年 3 月，纳入福建省医院 480 例 UUTC 患者。采用单因素分析、多重共线性筛选和 Lasso 分析构建与感染相关的红外波数评分（IR-infection score），预测术后感染。接着，采用 Delong 检验比较 IR-infection score 与传统指标的预测效能。然后，进行尿液宏基因组测序和结石培养，证明结石毒性与 IR-infection score 之间的相关性。最后，采用逻辑回归建立列线图。由四个独立波数组成的 IR-infection score 可准确预测术后感染（AUC=0.707）和脓毒症（AUC=0.824）。IR-infection score 的预测能力优于常用的临床指标。此外，宏基因组测序和结石培养证实了 IR-infection score 与结石毒性之间的相关性（均 P<0.05）。基于 IR-infection score 的列线图具有较高的预测效能（AUC 均>0.803）。本研究首次开发了一种新型的红外光谱标志物和列线图，有助于泌尿科医生更好地预测 UUTC 患者术后感染。
