Predictive performance of different kidney function estimation equations in lung transplant patients
2017
Abstract Background There has been limited examination of the performance of glomerular filtration rate estimation (eGFR) equations in lung transplant populations. This study aimed to compare the performance of serum creatinine and cystatin C based eGFR equations with Tc-99m diethylenetriaminepentaacetic acid (DTPA) GFR measurements in individuals with end-stage lung disease, either prior to, or following, lung transplantation. Methods In this prospective observational study, participants underwent GFR measurements with Tc-99m Pentetate. Measured results were compared with GFR estimates derived from estimation equations [4-variable Modification of Diet in Renal Disease, Cockcroft-Gault, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine, cystatin C and creatinine-cystatin C combined equations]. Results Ninety-seven individuals were studied (77 post- and 20 wait-listed for transplantation). Median (range) radionucleotide GFR was 56.7 ml/min/1.73 m 2 (22.8–109.2 ml/min/1.73 m 2 ). In the study cohort as a whole, the CKD-EPI creatinine-cystatin C combined equation showed the highest performance, but was only slightly superior to the CKD-EPI creatinine equation. However, in individuals with cystic fibrosis, low arm muscle mass and/or low body mass index, all of the creatinine-based equations showed unacceptable performance. In these subgroups, improved GFR estimation was seen with the CKD-EPI cystatin C equation, and predictions were better still using the CKD-EPI creatinine-cystatin C combined equation. Conclusions This study shows adequate predictive ability of CKD-EPI creatinine in the cohort as a whole, but unacceptable performance in patients with cystic fibrosis, low arm muscle mass and/or low body mass index. Our findings demonstrate that cystatin C may be a preferable filtration marker in these subgroups.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
48
References
10
Citations
NaN
KQI