Diagnostic standard: assessing glomerular filtration rate.
Pierre DelanayeHans PottelCavalier EtienneMartin FlamantThomas StehléChristophe MariatPublished in: Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association (2023)
Creatinine-based estimated GFR (eGFR) is imprecise at individual level, due to non-GFR-related serum creatinine determinants, including atypical muscle mass. Cystatin C has the advantage of being independent on muscle mass, a feature that led to the development of race- and sex-free equations. Yet, cystatin C-based equations do not perform better than creatinine-based equations to estimate GFR, unless both variables are included together. The new race-free Chronic Kidney Disease Epidemiology (CKD-EPI) equation, had slight opposite biases between Black and Non-Black subjects in USA, but performs poorer than that the previous version in European populations. The European Kidney Function Consortium (EKFC) equation developed in 2021 can be used both in children and adults, is more accurate in young and old adults, and is applicable to non-white European populations, by rescaling the Q factor, i.e. population median creatinine, in a potentially universal way. A sex- and race-free cystatin C-based EKFC, with the same mathematical design, has also be defined. New developments in the field of GFR estimation would be standardization of cystatin C assays, development of creatinine-based eGFR equations that would incorporate muscle mass data, implementation of new endogenous biomarkers, and the use of artificial intelligence. Standardization of different GFR measurement methods would also be a future challenge, as well as new technologies for measuring GFR. Future research is also needed on discrepancies between cystatin C and creatinine, which is associated with high risk of adverse events: standardize the definition of discrepancy, and understand its determinants.
Keyphrases
- uric acid
- artificial intelligence
- chronic kidney disease
- machine learning
- small cell lung cancer
- big data
- deep learning
- epidermal growth factor receptor
- end stage renal disease
- healthcare
- metabolic syndrome
- tyrosine kinase
- young adults
- primary care
- current status
- high resolution
- high throughput
- single cell
- genetic diversity