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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. |
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