ArticleEuropean journal of medical research2025
Risk factors for and a preliminary prediction model of coronary artery calcification in patients beginning hemodialysis.
Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
background and hypothesisVascular calcification (VC) is an important risk factor for cardiovascular events in patients undergoing maintenance hemodialysis (MHD); however, there is limited data on VC-related factors in patients beginning hemodialysis. Thus, this study aimed to determine the risk factors of VC and to establish a prediction model for evaluating VC progression in new patients undergoing hemodialysis.
methodsThis study selected 86 patients who initiated in-center MHD between March 2021 and November 2022. Demographic characteristics, medical history, and laboratory data were collected. Coronary artery calcification (CAC) was assessed based on the Agatston vascular score determined via computed tomography. Serum levels of the VC inhibitors fetuin-A was quantified via enzyme-linked immunosorbent assays. Univariate and multivariate regression analyses were conducted to determine the risk factors for VC, and a neural network-based approach was adopted to construct a VC prediction model.
resultsThe average age of the patients was 56.74 ± 12.79 years, and 65.1% were male. CAC was observed in 72.09% of patients. Age, body mass index, diabetes, the comorbidity index, and the number of coronary artery branches with calcification were positively correlated with the CAC score, whereas plasma fetuin-A levels was negatively correlated. The multivariate logistic regression analysis revealed that age [odds ratio (OR) 1.07, 95%CI 1.00-1.14], the comorbidity index [OR 1.72, 95%CI 1.16-2.57], diabetes [OR 3.97, 95%CI 1.16-13.58] were independent risk factors for CAC; these factors were used to establish a simple scoring model to predict VC risk.
conclusionAge, the comorbidity index, diabetes were identified as independent risk factors for CAC in patients beginning hemodialysis, and the new VC prediction model based on these factors may help identify VC in patients undergoing MHD, facilitating clinical interventions.
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