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Environmental science and pollution research international · 2022

Urinary cadmium and peripheral blood telomere length predict the risk of renal function impairment: a study of 547 community residents of Shanxi, China.

СтатьяНазвание и аннотация: Перевод в очереди
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Zhang Jia-Chen, Li Shuang-Jing, Guo Jian-Yong, Zhang Guo-Yan, Kang Hui, Shi Xiu-Jing, Zhou Han, Liang Yu-Fen, Shen Wei-Tong, Lei Li-Jian

Аннотация

Few reports have investigated the predictive value of urinary cadmium (UCd) and telomere length on renal function impairment. Therefore, we constructed nomogram models, using a cross-sectional survey to analyze the potential function of UCd and telomere length in renal function impairment risk. We randomly selected two community populations in Shanxi, China, and general information of the subjects was collected through face-to-face questionnaire surveys. Venous blood of subjects was collected to detect absolute telomere length (ATL) by real-time quantitative chain reaction (RT-PCR). Collecting urinary samples detected UCd and urinary N-acetyl-β-d-glucosaminidase (UNAG). Estimated glomerular filtration rate (eGFR) was obtained based on serum creatinine (SCr). Nomogram models on risk prediction analysis of renal function impairment was constructed. After adjusting for other confounding factors, UCd (β = 0.853, 95% confidence interval (CI): 0.739 ~ 0.986) and ATL (β = 1.803, 95%CI: 1.017 ~ 1.154) were independent risk influencing factors for increased UNAG levels, and the risk factors for eGFR reduction were UCd (β = 1.011, 95%CI: 1.187 ~ 1.471), age (β = 1.630, 95%CI: 1.303 ~ 2.038), and sex (β = 0.181, 95%CI: 0.105 ~ 0.310). Using UCd, ATL, sex, and age to construct the nomogram, and the C-statistics 0.584 (95%CI: 0.536 ~ 0.632) and 0.816 (95%CI: 0.781 ~ 0.851) were obtained by internal verification of the calibration curve, C-statistics revealed nomogram model validation was good and using decision curve analysis (DCA) confirmed a good predictive value of the nomogram models. In a nomogram model, ATL, UCd, sex, and age were detected as independent risk factors for renal function impairment, with UCd being the strongest predictor.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты