@article{FENG2026, 
author = {Jie FENG and Qiang QU and Xinyi LEI and Sitong CHEN and Zhipeng BAO and Zhi ZUO and Xinli LI and Hui WANG and Wenming YAO},
title = {Analysis of influencing factors and development of a prediction model for radiation dose in patients undergoing coronary angiography and percutaneous coronary intervention},
year = {2026},
journal = {Journal of Nanjing Medical University (Natural Sciences)},
volume = {46},
number = {8},
pages = {1218-1227},
keywords = {coronary heart disease, coronary angiography, percutaneous coronary intervention, radiation dose, analysis of influencing factors, prediction model},
url = {https://www.sciopen.com/article/10.7655/NYDXBNSN260138},
doi = {10.7655/NYDXBNSN260138},
abstract = {ObjectiveTo 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.MethodsA 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.ResultsThe 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 of170.1, MAE of 136.1, and R2 of 0.55. The calibration plot showed good agreement between the observed and predicted radiation doses.ConclusionThe 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.}
}