基于24h尿液代谢构建列线图模型预测高危泌尿系结石的复发

Establishing A Nomogram Model Based on 24h Urine Metabolism to Predict Recurrence of High-risk Urinary Stones

目的基于24 h尿液代谢,建立列线图,预测高危泌尿系结石复发风险。方法回顾性分析2018年7月至2019年10月在昆明医科大学第二附属医院泌尿外科行手术治疗的高危泌尿系结石患者的临床资料,采用Cox回归模型对患者的临床信息、病史及24 h尿液代谢特征进行单因素及多因素分析,基于独立危险因素建立列线图用于预测结石复发的风险。结果共200例高危患者纳入研究,男性137例(68.5%),女性63例(31.5%),平均年龄(46.64±13.09)岁,复发93例(46.5%),未复发107例(54.5%)。结论多因素Cox回归分析显示,饮水量、24 h枸橼酸、异常24 h尿pH是泌尿系结石复发的独立危险因素,并进一步建立可视化列线图模型(C-index为0.748)。建立一个用于预测高危泌尿系结石复发风险的列线图模型,该模型具有良好的鉴别能力,有助于临床医师为患者提供精准的个性化结石防治方案。

Objective To establish a nomogram based on 24-hour urine metabolism to predict the risk of recurrence of urinary stones. Methods The clinical data of high risk patients undergoing operation in the urology department of the Second Affiliated Hospital of Kunming Medical University from July 2018 to October 2019 were retrospectively analyzed. Univariate and multivariate Cox regression model were used to analyze the patients’ clinical information,medical history,and 24-hour urine metabolic characteristics. Based on independent risk factors, a nomogram was established to predict the risk of stone recurrence. Results A total of 200 patients were included in the study,137 males(68.5%),63 females(31.5%), with anaverage age of(46.64 ± 13.09) years old. 93 patients(46.5%) relapsed,and 107 patients(54.5%) did not relapse. Conclusion Multivariate Cox regression analysis showed that fluid intake, 24 h citric acid, and abnormal 24 h urine pH were independent risk factors for recurrence of urinary stones. A visual nomogram model(C-index 0.748) was established. The nomogram model for predicting the risk of recurrence of urinary stones has a good discrimination ability, and helps clinicians to provide patients with accurate personalized stone prevention and treatmentstratigy.