Suppr超能文献

通过随机尿样估算24小时尿磷排泄量。

Estimating 24-hour urine phosphate excretion from spot urine.

作者信息

Li Yongchao, Fuster Daniel G, Dhayat Nasser A, Seeger Harald, Ritter Alexander, Bonny Olivier, Wuerzner Gregoire, Ernandez Thomas, Segerer Stephan, Roth Beat, Rubio-Aliaga Isabel, Wagner Carsten A

机构信息

Institute of Physiology, University of Zurich, Zurich, Switzerland.

Department of Urology, Xiangya Hospital, Central South University, Changsha, China.

出版信息

Clin Kidney J. 2025 Apr 10;18(5):sfaf097. doi: 10.1093/ckj/sfaf097. eCollection 2025 May.

Abstract

BACKGROUND

24-hour urinary phosphate excretion (24hUrP) is indicative of intestinal phosphate absorption in steady-state conditions. Nevertheless, 24-hour urine collections are cumbersome and error-prone. Previous studies suggested that spot urine phosphate (uPi) could serve as a practical substitute to predict 24hUrP, however, these data originated only from patients with chronic kidney disease. Here, we investigated the validity of predictive equations using spot urine parameters to assess 24hUrP in a cohort with normal kidney function (eGFR >60 ml/min per 1.73 m) including 761 kidney stone patients and 207 non-kidney stone formers as assessed by low-dose CT scans, the Swiss Kidney Stone Cohort (SKSC).

METHODS

Published equations for 24hUrP were tested in our cohort and a novel predictive equation was developed. Pearson correlation coefficients and Bland-Altman plots were used to assess the relationship between spot uPi and spot urine creatinine (uCr) and 24hUrP. Additionally, forward multivariate analysis was performed to predict uPi excretion.

RESULTS

Previously published equations provided less accurate prediction of 24hUrP from spot urine. Log-transformed 24hUrP with log-transformed spot uPi and creatinine yielded the best model fit. In addition, inclusion of age, sex, and BMI significantly improved prediction of 24hUrP. Compared with spot uPi and uCr alone (  = 0.0561,  < .001) the new equation predicted 24hUrP (  = 0.1820,  < .001) more accurately.

CONCLUSIONS

Here, we present a new equation for predicting 24hUrP from spot urine samples of individuals with normal kidney function. This model has a moderate ability to explain 24hUrP variance but has the strength to use only parameters routinely collected in clinical settings such as spot urinary phosphate and creatinine, sex, BMI, and age.

摘要

背景

24小时尿磷排泄量(24hUrP)可反映稳态条件下肠道对磷的吸收情况。然而,收集24小时尿液既麻烦又容易出错。先前的研究表明,随机尿磷(uPi)可作为预测24hUrP的实用替代指标,不过,这些数据仅来源于慢性肾脏病患者。在此,我们在一个肾功能正常(估算肾小球滤过率>60 ml/min/1.73 m²)的队列中,通过低剂量CT扫描评估了761例肾结石患者和207例非肾结石形成者,即瑞士肾结石队列(SKSC),研究了使用随机尿参数预测24hUrP的预测方程的有效性。

方法

在我们的队列中测试已发表的24hUrP预测方程,并开发一个新的预测方程。使用Pearson相关系数和Bland-Altman图评估随机uPi与随机尿肌酐(uCr)及24hUrP之间的关系。此外,进行向前多变量分析以预测uPi排泄量。

结果

先前发表的方程对随机尿中24hUrP的预测准确性较低。对24hUrP、随机uPi和肌酐进行对数转换后得到的模型拟合效果最佳。此外,纳入年龄、性别和体重指数可显著提高对​​24hUrP的预测。与单独使用随机uPi和uCr相比(r = 0.0561,P <.001),新方程对24hUrP的预测更准确(r = 0.1820,P <.001)。

结论

在此,我们提出了一个根据肾功能正常个体的随机尿样预测24hUrP的新方程。该模型解释24hUrP变异性的能力中等,但优点是仅使用临床常规收集的参数,如随机尿磷和肌酐、性别、体重指数和年龄。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5292/12067064/6d6690a78ff7/sfaf097fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验