Lower kidney function is known to enhance cardiovascular disease (CVD) risk. It is unclear which estimated glomerular filtration rate (eGFR) equation best predict an increased CVD risk and if prediction can be improved by integration of multiple kidney function markers. We performed structural equation modeling (SEM) of kidney markers and compared the performance of the resulting pooled indexes with established eGFR equations to predict CVD risk in a 10-year longitudinal population-based design.
View Article and Find Full Text PDFBackground: Previous studies have proposed different formulas of estimating glomerular filtration rate (eGFR) among clinical patients. The comprehensive comparison of eGFR formulas is not well established in a Japanese population. We compared eGFR values and chronic kidney disease (CKD) classification of nine different eGFR in a Japanese general population sample.
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