Guo Bao-Liang, Ouyang Fu-Sheng, Yang Shao-Ming, Liu Zi-Wei, Lin Shao-Jia, Meng Wei, Huang Xi-Yi, Ouyang Li-Zhu, Chen Hai-Xiong, Hu Qiu-Gen
Department of Radiology, Shunde Hospital of Southern Medical University, The First People's Hospital of Shunde, Foshan, Guangdong, P.R. China.
Department of Radiology, Lecong Hospital of Shunde, Foshan, Guangdong, P.R. China.
Oncotarget. 2017 Aug 24;8(43):75087-75093. doi: 10.18632/oncotarget.20519. eCollection 2017 Sep 26.
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, = 7.23 × 10). 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.
大多数用于预测对比剂诱导的急性肾损伤(CI-AKI)的风险模型可用于对比剂暴露后预测,因此在实际应用中价值有限。我们旨在基于术前特征开发一种新型列线图,用于早期预测冠状动脉造影(CAG)或经皮冠状动脉介入治疗(PCI)术后患者的CI-AKI。回顾性分析了2015年1月至2017年1月期间的245例患者。应用最小绝对收缩和选择算子(Lasso)回归模型选择CI-AKI的最强预测因子。将每个患者的CI-AKI风险评分计算为所选预测因子的线性组合,并根据各自系数进行加权。通过C统计量评估列线图的辨别力。CI-AKI的发生率为13.9%(245例中有34例)。我们确定了10个预测因子,包括性别、糖尿病、乳酸脱氢酶水平、C反应蛋白、饮酒年限、慢性肾脏病(CKD)、CKD分期、中风、急性心肌梗死和收缩压。CI-AKI预测列线图具有良好的辨别力(C统计量,0.718,95%CI:0.637-0.800,P = 7.23×10)。CI-AKI风险评分的临界值为-1.953。因此,我们开发的新型列线图是一种简单、准确的工具,可用于术前预测接受CAG或PCI患者的CI-AKI。