Estimated Glomerular Filtration Rate in Chronic Kidney Disease: A Critical Review of Estimate-Based Predictions of Individual Outcomes in Kidney Disease

Abstract

Chronic kidney disease (CKD) is generally regarded as a final common pathway of several renal diseases, often leading to end-stage kidney disease (ESKD) and a need for renal replacement therapy. Estimated GFR (eGFR) has been used to predict this outcome recognizing its robust association with renal disease progression and the eventual need for dialysis in large, mainly cross-sectional epidemiological studies. However, GFR is implicitly limited as follows: (1) GFR reflects only one of the many physiological functions of the kidney; (2) it is dependent on several non-renal factors; (3) it has intrinsic variability that is a function of dietary intake, fluid and cardiovascular status, and blood pressure especially with impaired autoregulation or medication use; (4) it has been shown to change with age with a unique non-linear pattern; and (5) eGFR may not correlate with GFR in certain conditions and disease states. Yet, many clinicians, especially our non-nephrologist colleagues, tend to regard eGFR obtained from a simple laboratory test as both a valid reflection of renal function and a reliable diagnostic tool in establishing the diagnosis of CKD. What is the validity of these beliefs? This review will critically reassess the limitations of such single-focused attention, with a particular focus on inter-individual variability. What does science actually tell us about the usefulness of eGFR in diagnosing CKD?

Analysis of the association between glomerular filtration rate, proteinuria and metabolic syndrome in chronic kidney patients based on longitudinal data

“…Take two or three tubes, and the protein concentration of unknown samples was determined with the same method as above. The insulin resistance index (HOMA‐IR) was calculated by fasting blood glucose (mmol/L) × Fasting blood insulin (IU/L)/22.5. Glomerular filtration rate (EGFR) was calculated according to the CKD‐EPI formula [11]. CKD‐EPI formula: male: serum creatinine≤0.9 mL/dl, eGFR = 144 × (serum creatinine/0.9)−0.411 × 0.993 × age; serum creatinine>0.9 mL/dl, eGFR = 144 × (serum creatinine/0.9)−1.209 × 0.993 × age.…”

“…Glomerular filtration rate (EGFR) was calculated according to the CKD‐EPI formula [11]. CKD‐EPI formula: male: serum creatinine≤0.9 mL/dl, eGFR = 144 × (serum creatinine/0.9)−0.411 × 0.993 × age; serum creatinine>0.9 mL/dl, eGFR = 144 × (serum creatinine/0.9)−1.209 × 0.993 × age.…”

Energy Dynamics in Chronic Heart Failure, Chronic Kidney Disease & the Cardiorenal Syndrome: A New Causal Paradigm

“…In recent decades a statistically derived method has been widely used called estimated GFR (eGFR) that takes into account factors like age, gender, and body mass. A 2019 report analyzed 70 studies comparing eGFR with measured GFR in 40,000 renal transplant patients and showed that eGFR often varied by 30% or more and incorrectly staged 60% of CKD patients [291,292]. The eGFR method is but an estimate of an estimate.…”

Paper spray mass spectrometry combined with machine learning as a rapid diagnostic for chronic kidney disease

“…[8][9][10] For example, eGFR calculates kidney functionality based on serum creatinine levels and variables of sex and age to estimate glomerular filtration, and results may differ depending on non-kidney factors such as muscle mass and creatine supplementation. 11 ACR testing is generally performed in a spot urine sample and relies upon independent quantification of urinary albumin and creatinine by immunoturbidimetric and colourimetric methods, respectively. Turbid urine specimens, fever, time of collection and exercise can lead to uncertainty with albumin measurement, and storage of albumin calibrators can lead to albumin fragmentation and polymerization.…”