CT-derived Noncardiovascular Calcifications May Improve Coronary Heart Disease Prediction in Chronic Kidney Disease: The Multi-Ethnic Study of Atherosclerosis.

IF 4.5 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Elena Ghotbi, Quincy A Hathaway, David A Bluemke, Hamza Ahmed Ibad, Mahsima Shabani, Sepehr Akhtarkhavari, R Graham Barr, Wendy S Post, Matthew Budoff, Aarti Mathur, João A C Lima, Shadpour Demehri
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引用次数: 0

Abstract

Purpose To evaluate whether adding costal cartilage calcification (CCC) to coronary artery calcium (CAC) scores from chest CT improves coronary heart disease (CHD) prediction in patients with chronic kidney disease (CKD). Materials and Methods This study was a secondary analysis of the Multi-Ethnic Study of Atherosclerosis. Participants (April 2010 to January 2012) were stratified into low- and high-risk CKD groups based on Kidney Disease Improving Global Outcomes staging. CAC and CCC were measured from noncontrast CT scans. The primary outcome was incident CHD. Cox proportional hazards regression was performed for each group, with clinical risk factors and CAC (conventional CAC model), and with the addition of CCC (CCC model). Discriminative power was assessed using the area under the receiver operating characteristic curve (AUC). Results A total of 2355 participants (1314 female; median age, 68 years; IQR, 62-76) were included. Median baseline CAC scores were 22 (IQR, 0-183) and 133 (IQR, 20-649), and median CCC scores were 2055 (IQR, 900-4405) and 3187 (IQR, 1370-6516), for low- and high-risk CKD groups, respectively (P < .001 for CAC and P < .05 for CCC). The conventional CAC model showed lower discriminative power for CHD among the high-risk group (AUC, 0.70; 95% CI: 0.56, 0.84) versus the low-risk group (AUC, 0.74; 95% CI: 0.70, 0.78). Adding CCC improved the AUC to 0.75 (95% CI: 0.61, 0.89) in the high-risk group (P = .04), although there was no evidence of improved discrimination in the low-risk group (AUC, 0.74; 95% CI: 0.69, 0.78). Conclusion Clinical and conventional CAC models showed lower discriminative power for predicting CHD in the high-risk CKD group versus the low-risk group. In the high-risk group, adding CCC improved prediction over clinical models. Keywords: CT, Cardiac, Coronary Arteries, Coronary Artery Calcium Score, Costal Cartilage Calcification, Chronic Kidney Disease, Cardiovascular Disease, Coronary Heart Disease ClinicalTrials.gov identifier: NCT00005487 © RSNA, 2025.

ct衍生的非心血管钙化可能提高慢性肾脏疾病的冠心病预测:动脉粥样硬化的多民族研究
目的探讨在胸部CT冠状动脉钙化(CAC)评分中加入肋软骨钙化(CCC)评分是否能改善慢性肾脏疾病(CKD)患者对冠心病(CHD)的预测。材料与方法本研究是对动脉粥样硬化多民族研究的二次分析。参与者(2010年4月至2012年1月)根据肾脏疾病改善总体预后分期分为低危和高危CKD组。通过非对比CT扫描测量CAC和CCC。主要结局为偶发性冠心病。采用临床危险因素和CAC(常规CAC模型),并加入CCC (CCC模型),对各组进行Cox比例风险回归。判别力用受者工作特征曲线下面积(AUC)评估。结果共纳入受试者2355人,其中女性1314人,中位年龄68岁,IQR为62 ~ 76岁。中位基线CAC评分为22 (IQR, 0-183)和133 (IQR, 20-649),中位CCC评分分别为2055 (IQR, 900-4405)和3187 (IQR, 1370-6516),低和高风险CKD组(CAC和CCC分别P < 0.001和P < 0.05)。传统CAC模型显示,高危组(AUC, 0.70; 95% CI: 0.56, 0.84)与低危组(AUC, 0.74; 95% CI: 0.70, 0.78)相比,冠心病的鉴别能力较低。虽然没有证据表明在低风险组中(AUC, 0.74; 95% CI: 0.69, 0.78),但在高风险组中,添加CCC将AUC提高到0.75 (95% CI: 0.61, 0.89) (P = 0.04)。结论与低危组相比,临床CAC模型和常规CAC模型预测高危组冠心病的判别能力较低。在高危组中,添加CCC比临床模型更能改善预测。关键词:CT,心脏,冠状动脉,冠状动脉钙化评分,肋软骨钙化,慢性肾脏疾病,心血管疾病,冠心病ClinicalTrials.gov识别码:NCT00005487©RSNA, 2025。
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