Abstract

Cadmium-induced renal dysfunction varies between individuals. It would be valuable to figure out those susceptible individuals or predict the risk of cadmium induced renal dysfunction. In the present study, we used a nomogram model to identify high-risk of cadmium-induced renal tubular dysfunction. 342 subjects living in low and moderately cadmium polluted areas were included in this study. The daily cadmium intake from food (FCd) was estimated using food survey. The cadmium in blood (BCd) and urine (UCd) were detected by using flame atomic absorption spectrometry. Urinary β2Microglobulin (UBMG) was chosen as indicator of renal dysfunction. Logistic regression was used to select the independent risk factors for renal dysfunction. Bootstrap self-sampling and calibration curves were performed to quantify our modeling strategy. Age, sex, BCd and TCd were used to construct the nomogam in total population; age, BCd and TCd were adopted in women; age and BCd were used in men. The internal validation showed the C-index was 0.76 (95% 47 confidence interval (CI): 0.71–0.82) in total population, 0.74 (95% CI: 0.69–0.79) in men and 0.78 (95% CI: 0.72–0.84) in women. The area under the curve of the nomogram was 0.77 (95% CI: 0.71–0.83) in total population, 0.82(95% CI: 0.74–0.90) in women and 0.74(95% CI: 0.66–0.82) in men. Nomogram may be a rapid and simple risk assessment tool for predicting high-risk of renal tubular dysfunction in subjects exposed cadmium.

Highlights

  • We developed a nomogram model to predict the risk of cadmium-induced renal dysfunction with based on the independent risk factors

  • concordance index (C-index) and calibration curves all showed that the nomogram had acceptable predictive performance

  • The prevalence of renal tubular dysfunction increased with the increased BCd or urinary cadmium (UCd)

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Summary

Introduction

We used a nomogram model to identify high-risk of cadmium-induced renal tubular dysfunction. Several studies in Japan showed that renal tubular dysfunction was only observed in 20–32% of subjects living in cadmium polluted area[8] or 22–70% of female subjects with UCd of 5–30 μg/g cr[9]. Those data indicated that cadmium-induced renal dysfunction varies between individuals[10]. It would be interesting and valuable to establish a model to predict the renal tubular dysfunction in those population living in cadmium polluted area. We aimed to show the value of nomogram in predicting cadmium-induced renal dysfunction in a Chinese population

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