冠状动脉造影及介入治疗患者辐射剂量的影响因素分析及预测模型构建
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南京医科大学第一附属医院心内科, 江苏 南京 210029

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R814.2

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国家自然科学基金(82370389,81970339);国家高技术研究发展计划(2017YFC1700505)


Analysis of influencing factors and development of a prediction model for radiation dose in patients undergoing coronary angiography and percutaneous coronary intervention
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Department of Cardiology, the First Affiliated Hospital with Nanjing Medical University, Nanjing 210029 , China

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    摘要:

    目的:探究影响冠状动脉造影(coronary angiography,CAG)及介入治疗(percutaneous coronary intervention,PCI)患者辐射剂量的因素,并构建辐射剂量的临床预测模型。方法:回顾性纳入2020年1月—2024年12月于南京医科大学第一附属医院就诊并行CAG的293例阻塞性冠心病患者,按7:3比例随机分为训练集(208例)和测试集(85例)。以术中辐射剂量为结局,基于临床特征及介入相关变量,采用多种变量筛选和建模方法建立多因素线性回归预测模型并构建列线图,在测试集中采用均方根误差(root mean square error,RMSE)、平均绝对误差(mean absolute error,MAE)、决定系数R²和校准曲线评价模型性能。结果:最终模型纳入年龄、体重指数(body mass index,BMI)、甘油三酯、高密度脂蛋白胆固醇(high-density lipoprotein cholesterol,HDL-C)、左室舒张末期内径(left ventricular end-diastolic diameter,LVDd)、左室射血分数(left ventricular ejection fraction,LVEF)、手术时间及透视时间8个变量。多因素分析显示BMI、LVDd、LVEF、手术时间和透视时间与辐射剂量呈正相关,HDL-C与辐射剂量呈负相关。模型在测试集中表现良好,RMSE为170.1,MAE为136.1,R²为0.55。校准曲线显示观测值与预测值的一致性较好。结论:基于常规可获得的临床特征及介入相关指标构建的辐射剂量预测模型在内部验证中具有较好的预测性能,可为CAG及PCI患者的辐射剂量风险评估和剂量管理提供参考。

    Abstract:

    Objective: To investigate the influencing factors of radiation dose in patients undergoing coronary angiography (CAG) and percutaneous coronary intervention (PCI), and to develop a clinical prediction model for radiation dose. Methods: A total of 293 patients with obstructive coronary artery disease who underwent CAG at the First Affiliated Hospital of Nanjing Medical University from January 2020 to December 2024 were retrospectively enrolled. Patients were randomly divided into a training set (n=208) and a testing set (n=85) at a ratio of 7:3. Intraoperative radiation dose was defined as the outcome variable. Based on clinical characteristics and interventional procedure-related variables, multiple variable selection and modeling methods were applied to establish a multivariable linear regression prediction model, and a nomogram was constructed. Model performance was evaluated in the testing set using the root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²), and calibration plot. Results: The final model included age, body mass index(BMI), triglycerides, high-density lipoprotein cholesterol (HDL-C), left ventricular end-diastolic diameter(LVDd), left ventricular ejection fraction (LVEF), procedure time, and fluoroscopy time. Multivariate analysis showed that BMI, LVDd, LVEF, procedure time, and fluoroscopy time were positively associated with radiation dose, whereas HDL-C was negatively associated with radiation dose. The model demonstrated good predictive performance in the testing set, with an RMSE of 170.1, MAE of 136.1, and R² of 0.55. The calibration plot showed good agreement between the observed and predicted radiation doses. Conclusion: The radiation dose prediction model based on routinely available clinical and interventional variables showed good predictive performance in internal validation, and may provide a useful reference for radiation risk assessment and dose management in patients undergoing CAG and PCI.

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冯婕,渠强,雷心仪,等.冠状动脉造影及介入治疗患者辐射剂量的影响因素分析及预测模型构建[J].南京医科大学学报(自然科学版),2026,46(8):1218-1227,1268

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  • 收稿日期:2026-01-26
  • 最后修改日期:2026-04-21
  • 录用日期:2026-04-29
  • 在线发布日期: 2026-08-07
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