Risk factors for and a preliminary prediction model of coronary artery calcification in patients beginning hemodialysis.

IF 2.8 3区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Hao Xiong, Cuifang Sun, Jie Song, Yan Yu, Chang Wang, Fang Yuan
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引用次数: 0

Abstract

Background and hypothesis: Vascular 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.

Methods: This 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.

Results: The 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.

Conclusion: Age, 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.

开始血液透析患者冠状动脉钙化的危险因素及初步预测模型。
背景与假设:血管钙化(VC)是维持性血液透析(MHD)患者心血管事件的重要危险因素;然而,在开始血液透析的患者中,vc相关因素的数据有限。因此,本研究旨在确定VC的危险因素,并建立评估血液透析新患者VC进展的预测模型。方法:本研究选择了2021年3月至2022年11月期间启动中心MHD的86例患者。收集了人口统计学特征、病史和实验室数据。冠状动脉钙化(CAC)的评估基于计算机断层扫描测定的Agatston血管评分。通过酶联免疫吸附法测定血清VC抑制剂胎蛋白a的水平。通过单因素和多因素回归分析确定风险因素,并采用基于神经网络的方法构建风险预测模型。结果:患者平均年龄56.74±12.79岁,男性占65.1%。72.09%的患者出现CAC。年龄、体重指数、糖尿病、合并症指数、冠状动脉钙化分支数与CAC评分呈正相关,而血浆胎儿素a水平与CAC评分呈负相关。多因素logistic回归分析显示,年龄[比值比(OR) 1.07, 95%CI 1.00 ~ 1.14]、合并症指数[OR 1.72, 95%CI 1.16 ~ 2.57]、糖尿病[OR 3.97, 95%CI 1.16 ~ 13.58]是CAC的独立危险因素;利用这些因素建立了预测VC风险的简单评分模型。结论:年龄、合并症指数、糖尿病是血液透析患者CAC的独立危险因素,基于这些因素的新的VC预测模型有助于识别MHD患者的VC,为临床干预提供依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
European Journal of Medical Research
European Journal of Medical Research 医学-医学:研究与实验
CiteScore
3.20
自引率
0.00%
发文量
247
审稿时长
>12 weeks
期刊介绍: European Journal of Medical Research publishes translational and clinical research of international interest across all medical disciplines, enabling clinicians and other researchers to learn about developments and innovations within these disciplines and across the boundaries between disciplines. The journal publishes high quality research and reviews and aims to ensure that the results of all well-conducted research are published, regardless of their outcome.
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