OBJECTIVES: We sought to develop a simple risk score of contrast-induced nephropathy (CIN) after percutaneous coronary intervention (PCI). BACKGROUND: Although several risk factors for CIN have been identified, the cumulative risk rendered by their combination is unknown. METHODS: A total of 8,357 patients were randomly assigned to a development and a validation dataset. The baseline clinical and procedural characteristics of the 5,571 patients in the development dataset were considered as candidate univariate predictors of CIN (increase >or=25% and/or >or=0.5 mg/dl in serum creatinine at 48 h after PCI vs. baseline). Multivariate logistic regression was then used to identify independent predictors of CIN with a p value <0.0001. Based on the odds ratio, eight identified variables (hypotension, intra-aortic balloon pump, congestive heart failure, chronic kidney disease, diabetes, age >75 years, anemia, and volume of contrast) were assigned a weighted integer; the sum of the integers was a total risk score for each patient. RESULTS: The overall occurrence of CIN in the development set was 13.1% (range 7.5% to 57.3% for a low [<or=5] and high [>or=16] risk score, respectively); the rate of CIN increased exponentially with increasing risk score (Cochran Armitage chi-square, p < 0.0001). In the 2,786 patients of the validation dataset, the model demonstrated good discriminative power (c statistic = 0.67); the increasing risk score was again strongly associated with CIN (range 8.4% to 55.9% for a low and high risk score, respectively). CONCLUSIONS: The risk of CIN after PCI can be simply assessed using readily available information. This risk score can be used for both clinical and investigational purposes.
RCT Entities:
OBJECTIVES: We sought to develop a simple risk score of contrast-induced nephropathy (CIN) after percutaneous coronary intervention (PCI). BACKGROUND: Although several risk factors for CIN have been identified, the cumulative risk rendered by their combination is unknown. METHODS: A total of 8,357 patients were randomly assigned to a development and a validation dataset. The baseline clinical and procedural characteristics of the 5,571 patients in the development dataset were considered as candidate univariate predictors of CIN (increase >or=25% and/or >or=0.5 mg/dl in serum creatinine at 48 h after PCI vs. baseline). Multivariate logistic regression was then used to identify independent predictors of CIN with a p value <0.0001. Based on the odds ratio, eight identified variables (hypotension, intra-aortic balloon pump, congestive heart failure, chronic kidney disease, diabetes, age >75 years, anemia, and volume of contrast) were assigned a weighted integer; the sum of the integers was a total risk score for each patient. RESULTS: The overall occurrence of CIN in the development set was 13.1% (range 7.5% to 57.3% for a low [<or=5] and high [>or=16] risk score, respectively); the rate of CIN increased exponentially with increasing risk score (Cochran Armitage chi-square, p < 0.0001). In the 2,786 patients of the validation dataset, the model demonstrated good discriminative power (c statistic = 0.67); the increasing risk score was again strongly associated with CIN (range 8.4% to 55.9% for a low and high risk score, respectively). CONCLUSIONS: The risk of CIN after PCI can be simply assessed using readily available information. This risk score can be used for both clinical and investigational purposes.
Authors: Paolo Calabrò; Renatomaria Bianchi; Mario Crisci; Mario Caprile; Maurizio Cappelli Bigazzi; Rosalinda Palmieri; Enrica Golia; Anna De Vita; Ilaria Jane Romano; Giuseppe Limongelli; Maria Giovanna Russo; Raffaele Calabrò Journal: Intern Emerg Med Date: 2011-01-29 Impact factor: 3.397