Development and validation of a new equation based on plasma creatinine and muscle mass assessed by CT scan to estimate glomerular filtration rate: a cross-sectional study

ABSTRACT Background Inter-individual variations of non-glomerular filtration rate (GFR) determinants serum creatinine, such as muscle mass, account for the imperfect performance estimated GFR (eGFR) equations. We aimed to develop an equation based on creatinine and total lumbar cross-sectional area measured by unenhanced computed tomography scan at third vertebra. Methods The mass–based eGFR (MMB-eGFR) was developed in 118 kidney donor candidates (iohexol clearance) using linear regression. Validation cohorts included 114 healthy subjects from another center (51Cr-EDTA clearance, validation population 1), 55 patients with chronic diseases (iohexol, 2), 60 highly discordant cystatin C–based eGFR, thus presumed have atypical non-GFR (51Cr-EDTA, 3). Mean bias mean difference between GFR, precision standard deviation (SD) bias, accuracy percentage values falling within 20% 30% GFR. Results In 1, MMB-eGFR not different those CKD-EPICr2009 CKD-EPICr2021. 2, unbiased displayed better than CKD-EPICr2009, CKD-EPICr2021 EKFC (SD biases: 13.1 vs 16.5, 16.8 15.9 mL/min/1.73 m2). 3, had {accuracy 30%: 75.0% [95% confidence interval (CI) 64.0–86.0] 51.5% (95% CI 39.0–64.3) 43.3% 31.0–55.9) CKD-EPICr2021, 53.3% 40.7–66.0) EKFC}. Difference Black white ?2.1 m2 ?7.2 3.0), ?8.4 ?13.2 ?3.6) Conclusion performances equations demographics, could be applied various ethnic backgrounds.