BACKGROUND: Beta-trace protein (BTP) is a low molecular weight glycoprotein that is a more sensitive marker of glomerular filtration rate (GFR) than serum creatinine. The utility of BTP has been limited by the lack of an equation to translate BTP into an estimate of GFR. The objectives of this study were to develop a BTP-based GFR estimation equation. METHODS: We measured BTP and GFR by (99m)technetium-diethylenetriaminepentaacetic acid in 163 stable adult renal transplant recipients. Stepwise multiple regression models were created to predict GFR corrected for body surface area. The following variables were considered for entry into the model: BTP, urea, sex, albumin, creatinine, age, and race. RESULTS: BTP alone accounted for 75.6% of variability in GFR. The model that included all the predictor variables had the largest coefficient of determination (R(2)) at 0.821. The model with only BTP, urea, and sex had only a slightly lower R(2) of 0.81 and yielded the following equation: GFR mL . min(-1) . (1.73 m(2))(-1) = 112.1 x BTP(-0.662) x Urea(-0.280) x (0.88 if female). A 2nd equation (R(2) = 0.79) using creatinine instead of urea was also developed: GFR mL . min(-1) . (1.73 m(2))(-1) = 1.678 x BTP(-0.758) x creatinine(-0.204) x (0.871 if female). CONCLUSIONS: We have shown that BTP can be used in a simple equation to estimate GFR. Further study is needed in other populations to determine accuracy and clinical utility of this equation.
BACKGROUND:Beta-trace protein (BTP) is a low molecular weight glycoprotein that is a more sensitive marker of glomerular filtration rate (GFR) than serum creatinine. The utility of BTP has been limited by the lack of an equation to translate BTP into an estimate of GFR. The objectives of this study were to develop a BTP-based GFR estimation equation. METHODS: We measured BTP and GFR by (99m)technetium-diethylenetriaminepentaacetic acid in 163 stable adult renal transplant recipients. Stepwise multiple regression models were created to predict GFR corrected for body surface area. The following variables were considered for entry into the model: BTP, urea, sex, albumin, creatinine, age, and race. RESULTS:BTP alone accounted for 75.6% of variability in GFR. The model that included all the predictor variables had the largest coefficient of determination (R(2)) at 0.821. The model with only BTP, urea, and sex had only a slightly lower R(2) of 0.81 and yielded the following equation: GFR mL . min(-1) . (1.73 m(2))(-1) = 112.1 x BTP(-0.662) x Urea(-0.280) x (0.88 if female). A 2nd equation (R(2) = 0.79) using creatinine instead of urea was also developed: GFR mL . min(-1) . (1.73 m(2))(-1) = 1.678 x BTP(-0.758) x creatinine(-0.204) x (0.871 if female). CONCLUSIONS: We have shown that BTP can be used in a simple equation to estimate GFR. Further study is needed in other populations to determine accuracy and clinical utility of this equation.
Authors: Navdeep Tangri; Lesley A Inker; Hocine Tighiouart; Eric Sorensen; Vandana Menon; Gerald Beck; Michael Shlipak; Josef Coresh; Andrew S Levey; Mark J Sarnak Journal: J Am Soc Nephrol Date: 2011-12-15 Impact factor: 10.121
Authors: Brad C Astor; Tariq Shafi; Ron C Hoogeveen; Kunihiro Matsushita; Christie M Ballantyne; Lesley A Inker; Josef Coresh Journal: Am J Kidney Dis Date: 2012-02-04 Impact factor: 8.860
Authors: Tariq Shafi; Wieneke M Michels; Andrew S Levey; Lesley A Inker; Friedo W Dekker; Raymond T Krediet; Tiny Hoekstra; George J Schwartz; John H Eckfeldt; Josef Coresh Journal: Kidney Int Date: 2016-01-21 Impact factor: 10.612
Authors: Nrupen A Bhavsar; Lawrence J Appel; John W Kusek; Gabriel Contreras; George Bakris; Josef Coresh; Brad C Astor Journal: Am J Kidney Dis Date: 2011-09-22 Impact factor: 8.860
Authors: Lesley A Stevens; Christopher H Schmid; Tom Greene; Yaping Lucy Zhang; Gerald J Beck; Marc Froissart; Lee L Hamm; Julia B Lewis; Michael Mauer; Gerjan J Navis; Michael W Steffes; Paul W Eggers; Josef Coresh; Andrew S Levey Journal: Am J Kidney Dis Date: 2010-06-16 Impact factor: 8.860
Authors: Takeki Suzuki; Sunil K Agarwal; Rajat Deo; Nona Sotoodehnia; Morgan E Grams; Elizabeth Selvin; Hugh Calkins; Wayne Rosamond; Gordon Tomaselli; Josef Coresh; Kunihiro Matsushita Journal: Am Heart J Date: 2016-07-14 Impact factor: 4.749