Research Papers:

Development of a preprocedure nomogram for predicting contrast-induced acute kidney injury after coronary angiography or percutaneous coronary intervention

Bao-Liang Guo, Fu-Sheng Ouyang, Shao-Ming Yang, Zi-Wei Liu, Shao-Jia Lin, Wei Meng, Xi-Yi Huang, Li-Zhu Ouyang, Hai-Xiong Chen _ and Qiu-Gen Hu

PDF  |  HTML  |  How to cite  |  Order a Reprint

Oncotarget. 2017; 8:75087-75093. https://doi.org/10.18632/oncotarget.20519

Metrics: PDF 1388 views  |   HTML 1643 views  |   ?  


Bao-Liang Guo1,*, Fu-Sheng Ouyang1,*, Shao-Ming Yang1, Zi-Wei Liu1, Shao-Jia Lin, Wei Meng1, Xi-Yi Huang2, Li-Zhu Ouyang1, Hai-Xiong Chen1 and Qiu-Gen Hu1

1Department of Radiology, Shunde Hospital of Southern Medical University, The First People’s Hospital of Shunde, Foshan, Guangdong, P.R. China

2Department of Radiology, Lecong Hospital of Shunde, Foshan, Guangdong, P.R. China

*These authors have contributed equally to this work

Correspondence to:

Hai-Xiong Chen, email: 13825553451@139.com

Qiu-Gen Hu, email: qiugenhu@126.com

Keywords: contrast-induced acute kidney injury, nomogram, coronary angiography, percutaneous coronary intervention

Received: June 06, 2017    Accepted: August 04, 2017    Published: August 24, 2017


Most of the risk models for predicting contrast-induced acute kidney injury (CI-AKI) are available for postcontrast exposure prediction, thus have limited values in practice. We aimed to develop a novel nomogram based on preprocedural features for early prediction of CI-AKI in patients after coronary angiography (CAG) or percutaneous coronary intervention (PCI). A total of 245 patients were retrospectively reviewed from January 2015 to January 2017. Least absolute shrinkage and selection operator (Lasso) regression model was applied to select most strong predictors for CI-AKI. The CI-AKI risk score was calculated for each patient as a linear combination of selected predictors that were weighted by their respective coefficients. The discrimination of nomogram was assessed by C-statistic. The occurrence of CI-AKI was 13.9% (34 out of 245). We identified ten predictors including sex, diabetes mellitus, lactate dehydrogenase level, C-reactive protein, years since drinking, chronic kidney disease (CKD), stage of CKD, stroke, acute myocardial infarction, and systolic blood pressure. The CI-AKI prediction nomogram obtained good discrimination (C-statistic, 0.718, 95%CI: 0.637-0.800, p = 7.23 × 10-5). The cutoff value of CI-AKI risk score was -1.953. Accordingly, the novel nomogram we developed is a simple and accurate tool for preprocedural prediction of CI-AKI in patients undergoing CAG or PCI.

Creative Commons License All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.
PII: 20519