A novel risk assessment model of contrast-induced nephropathy after percutaneous coronary intervention in patients with diabetes

被引:11
作者
Yao, Zhi-Feng [1 ,2 ]
Shen, Hong [3 ]
Tang, Min-Na [1 ,2 ]
Yan, Yan [1 ,2 ]
Ge, Jun-Bo [1 ,2 ]
机构
[1] Fudan Univ, Zhongshan Hosp, Dept Cardiol, Shanghai, Peoples R China
[2] Shanghai Inst Cardiovasc Dis, Shanghai, Peoples R China
[3] Fudan Univ, Zhongshan Hosp, Dept Emergency Med, Shanghai, Peoples R China
关键词
contrast-induced nephropathy; major adverse cardiovascular events; percutaneous coronary intervention; risk scores; ELEVATION MYOCARDIAL-INFARCTION; SCORE; HYPERGLYCEMIA; PREDICTION;
D O I
10.1111/bcpt.13501
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
The purpose of our study was to develop a simple clinical pre-procedure risk model based on clinical characteristics for the prediction of contrast-induced nephropathy (CIN) and major adverse cardiac events (MACEs) after percutaneous coronary intervention (PCI) in patients with diabetes. A total of 1113 patients with diabetes who underwent PCI with contrast exposure were randomized into a development group (n = 742) and a validation group (n = 371) in a 2:1 ratio. CIN was defined as an increase of either 25% or 0.5 mg/dL (44.2 mu mol/L) in serum creatinine within 72 hours after contrast infusion. A simple CIN risk score based on independent predictors was established. Four variables were identified for our risk score model: LVEF < 40%, acute coronary syndrome (ACS), eGFR < 60, and contrast volume > 300 mL. Based on this new CIN risk score, the incidence of CIN had a significant trend with increased predicting score values of 5.9%, 32.9% and 60.0%, corresponding to low-, moderate- and high-risk groups, respectively. The novel risk assessment exhibited moderate discrimination ability for predicting CIN, with an AUC of 0.759 [95% CI 0.668-0.852,P = .001] in the validation cohort. It also had similar prognostic values for one-year follow-up MACE (C-statistic: 0.705 and 0.606 for new risk score and Mehran score, respectively). This novel risk prediction model could be effective for preventing nephropathy in diabetic patients receiving contrast media during surgical procedures.
引用
收藏
页码:305 / 314
页数:10
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