AI辅助评估慢性肾脏病分期与胸部CT冠脉钙化积分的进展及风险因素

The Progress and Risk Factors of AI Assisted Evaluation of Chronic Kidney Disease Staging and Chest CT Coronary Artery Calcification Score

摘要: 慢性肾脏病(Chronic Kidney Disease, CKD)患者心血管疾病风险显著增加，其中冠状动脉钙化(CAC)是重要预测指标。传统评估方法存在局限性，而人工智能技术为CKD分期与冠脉钙化积分(CACS)的评估提供了新思路。本文综述了AI在CKD患者冠脉钙化评估中的应用进展，包括自动化CACS计算、风险因素分析及预后预测等方面。AI模型显示出与传统方法高度相关性，同时提高了评估效率和准确性。此外，本文还探讨了CKD分期与CACS进展的相关性及影响因素，如钙磷代谢异常、传统心血管危险因素等。AI辅助评估为CKD患者心血管风险管理提供了更精准的工具，有望改善临床决策和患者预后。

Abstract: Patients with chronic kidney disease (CKD) have a significantly increased risk of cardiovascular disease, with coronary artery calcification (CAC) being an important predictor. Traditional evaluation methods have limitations, while artificial intelligence technology provides new ideas for the assessment of CKD staging and coronary artery calcification score (CACS). This article reviews the application progress of AI in the assessment of coronary artery calcification in CKD patients, including automated CACS calculation, risk factor analysis, and prognosis prediction. The AI model shows a high correlation with traditional methods, while improving evaluation efficiency and accuracy. In addition, this article also explores the correlation and influencing factors between CKD staging and CACS progression, such as abnormal calcium and phosphorus metabolism, traditional cardiovascular risk factors, etc. AI assisted assessment provides more accurate tools for cardiovascular risk management in CKD patients, which is expected to improve clinical decision-making and patient prognosis.