Zhonghan Ni1, Yan Liang2, Nianjin Xie1, Jin Liu1, Guoli Sun1, Shiqun Chen1, Jianfeng Ye3, Yibo He1, Wei Guo1, Ning Tan1, Jiyan Chen1, Yong Liu1, Zhujun Chen1, Shouhong Wang4. 1. Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China. 2. Department of Cardiology, Maoming People's Hospital, Maoming 525000, China. 3. Department of Cardiology, Dongguan People's Hospital, Dongguan 523059, China. 4. Department of Critical Care Medicine, Guangdong Geriatric Institute, Guangdong Provincial People's Hospital and Guangdong Academy of Medical Sciences, Guangzhou 510080, China.
Abstract
BACKGROUND: A few simple and pre-procedural risk models have been developed for predicting contrast-induced nephropathy (CIN), which allow for early administration of preventative strategies before coronary angiography (CAG). The study aims to develop and validate simple pre-procedure tools for predicting risk of CIN following CAG. METHODS: We retrospectively analyzed the data from 3,469 consecutive patients undergoing CAG, who were randomly assigned to a development dataset (n=2,313) and a validation dataset (n=1,156). CIN was defined as an increase in serum creatinine (SCr) ≥0.5 mg/dL from baseline within 72 hours after CAG. Multivariate logistic regression was applied to identify independent predictors of CIN to develop risk models. The possible predictors included age >75 years, hypotension, acute myocardial infarction (AMI), SCr ≥1.5 mg/dL, and congestive heart failure (CHF). RESULTS: The incidences of CIN were 3.20% and 3.55% in the training and validation dataset respectively. Compared to classical Mehran' and ACEF CIN risk score, the new score across the validation dataset exhibited similar discrimination and predictive ability on CIN (c-statistic: 0.829, 0.832, 0.812 respectively) and in-hospital mortality (c-statistic: 0.909, 0.937, 0.866 respectively) (all P>0.05). CONCLUSIONS: The easy-to-use pre-procedural prediction model only containing 5 factors had similar predictive ability on CIN and mortality.
BACKGROUND: A few simple and pre-procedural risk models have been developed for predicting contrast-induced nephropathy (CIN), which allow for early administration of preventative strategies before coronary angiography (CAG). The study aims to develop and validate simple pre-procedure tools for predicting risk of CIN following CAG. METHODS: We retrospectively analyzed the data from 3,469 consecutive patients undergoing CAG, who were randomly assigned to a development dataset (n=2,313) and a validation dataset (n=1,156). CIN was defined as an increase in serum creatinine (SCr) ≥0.5 mg/dL from baseline within 72 hours after CAG. Multivariate logistic regression was applied to identify independent predictors of CIN to develop risk models. The possible predictors included age >75 years, hypotension, acute myocardial infarction (AMI), SCr ≥1.5 mg/dL, and congestive heart failure (CHF). RESULTS: The incidences of CIN were 3.20% and 3.55% in the training and validation dataset respectively. Compared to classical Mehran' and ACEF CIN risk score, the new score across the validation dataset exhibited similar discrimination and predictive ability on CIN (c-statistic: 0.829, 0.832, 0.812 respectively) and in-hospital mortality (c-statistic: 0.909, 0.937, 0.866 respectively) (all P>0.05). CONCLUSIONS: The easy-to-use pre-procedural prediction model only containing 5 factors had similar predictive ability on CIN and mortality.
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