BACKGROUND: Previous risk score is not simple for predicting existence of atherosclerotic renal artery stenosis (ARAS). Our study aims to develop a simple score to predict ARAS in eastern people with ischemic heart disease. METHODS: There were two data sources involved in this study. From the data source of patients with acute myocardial infarction, we developed a clinical score for predicting existence of ARAS. After this, we validated this clinical score in data source of patients with ischemic heart failure. RESULTS: By multivariable logistic regression analysis, only age, hypertension, stroke or intermittent claudication, serum creatinine were involved in this model. Receiver operating characteristic curve was plotted. In the first data source, area under curve is 0.808 to predict ARAS, and 0.762 for bilateral ARAS. In the second data source, area under curve is 0.721 to predict ARAS, and 0.827 for ARAS. Cutoff value of 35.0 yields a sensitivity of 82.4% and a specificity of 51.0% for ARAS, a sensitivity of 78.9% and a specificity of 47.1% for bilateral ARAS. In the second data source, this cutoff value yields a sensitivity of 85.0% and a specificity of 30.5% for ARAS, a sensitivity of 85.7% and a specificity of 17.5% for bilateral ARAS. CONCLUSIONS: We have developed a simple score for eastern people to predicting existence of ARAS with acceptable sensitivity and specificity in patients with ischemic heart disease. This score is still needed to be validated in general population or patients with no coronary heart disease.
BACKGROUND: Previous risk score is not simple for predicting existence of atherosclerotic renal artery stenosis (ARAS). Our study aims to develop a simple score to predict ARAS in eastern people with ischemic heart disease. METHODS: There were two data sources involved in this study. From the data source of patients with acute myocardial infarction, we developed a clinical score for predicting existence of ARAS. After this, we validated this clinical score in data source of patients with ischemic heart failure. RESULTS: By multivariable logistic regression analysis, only age, hypertension, stroke or intermittent claudication, serum creatinine were involved in this model. Receiver operating characteristic curve was plotted. In the first data source, area under curve is 0.808 to predict ARAS, and 0.762 for bilateral ARAS. In the second data source, area under curve is 0.721 to predict ARAS, and 0.827 for ARAS. Cutoff value of 35.0 yields a sensitivity of 82.4% and a specificity of 51.0% for ARAS, a sensitivity of 78.9% and a specificity of 47.1% for bilateral ARAS. In the second data source, this cutoff value yields a sensitivity of 85.0% and a specificity of 30.5% for ARAS, a sensitivity of 85.7% and a specificity of 17.5% for bilateral ARAS. CONCLUSIONS: We have developed a simple score for eastern people to predicting existence of ARAS with acceptable sensitivity and specificity in patients with ischemic heart disease. This score is still needed to be validated in general population or patients with no coronary heart disease.
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