International urology and nephrology · 2025
Development and validation of a nomogram for predicting abdominal aortic calcification in maintenance hemodialysis patients.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Yu Miao, Bao Xiaoyan, Qian Xinfeng
Аннотация
OBJECTIVE: Develop and validate a nomogram for predicting abdominal aortic calcification (AAC) in maintenance hemodialysis (MHD) patients. The purpose is to provide a visual predictive assessment tool for the occurrence of AAC in MHD patients and assist doctors in early identification of high-risk populations for AAC.
METHODS: This retrospective cross-sectional study collected 334 end-stage renal disease patients who underwent MHD treatment in the hospital for ≥ 3 months from January 2022 to March 2025. They were randomly divided into a training cohort (n = 200) and an internal validation cohort (n = 134) in a 6:4 ratio. Single factor and multiple factor logistic regression analysis were used to analyze the characteristics of the training cohort, and it was transformed into the nomogram risk model of AAC. The discriminative and calibration abilities of nomogram were validated in the training cohort and validation cohort through receiver operating characteristic under the curve (AUC) and Hosmer Lemeshow (H-L) test.
RESULTS: The incidence of AAC is 71.0% (237/334). We identified six independent risk factors for predicting AAC, including age, dialysis vintage, high-sensitivity C-reactive protein, calcium, intact parathyroid hormone, and 25 hydroxyvitamin D (25(OH)D). The nomogram showed sufficient prediction accuracy, with AUC values of 0.918 (95% CI: 0.870-0.967) and 0.826 (95% CI: 0.742-0.869) in the training cohort and validation cohort, respectively. The results of the H-L test fit well.
CONCLUSIONS: We have developed and validated an easy-to-use nomogram to predict the occurrence of AAC in MHD patients. It helps identify high-risk populations.
METHODS: This retrospective cross-sectional study collected 334 end-stage renal disease patients who underwent MHD treatment in the hospital for ≥ 3 months from January 2022 to March 2025. They were randomly divided into a training cohort (n = 200) and an internal validation cohort (n = 134) in a 6:4 ratio. Single factor and multiple factor logistic regression analysis were used to analyze the characteristics of the training cohort, and it was transformed into the nomogram risk model of AAC. The discriminative and calibration abilities of nomogram were validated in the training cohort and validation cohort through receiver operating characteristic under the curve (AUC) and Hosmer Lemeshow (H-L) test.
RESULTS: The incidence of AAC is 71.0% (237/334). We identified six independent risk factors for predicting AAC, including age, dialysis vintage, high-sensitivity C-reactive protein, calcium, intact parathyroid hormone, and 25 hydroxyvitamin D (25(OH)D). The nomogram showed sufficient prediction accuracy, with AUC values of 0.918 (95% CI: 0.870-0.967) and 0.826 (95% CI: 0.742-0.869) in the training cohort and validation cohort, respectively. The results of the H-L test fit well.
CONCLUSIONS: We have developed and validated an easy-to-use nomogram to predict the occurrence of AAC in MHD patients. It helps identify high-risk populations.