Assessment of Glomerular Filtration Rate (GFR) Estimation Methods in Patients With Obesity
Authors' conclusion
In patients with overweight or obesity, the EKFC equation performed worse than the ML-based models and the CKD-EPI 2021 equation despite limitations of the latter in European populations. Our findings highlight the need for more accurate GFR estimation in this population, optimization of these models, and their validation in larger, more diverse cohorts.
Study context
- Population
- Cohort of patients with overweight or obesity
- Comparison
- European Kidney Function Consortium (EKFC) equation vs CKD-EPI 2021 equation vs machine learning models, against measured GFR
- Outcome
- Median bias (estimated GFR (eGFR) minus mGFR) and concordance correlation coefficient
Performance
As reported in the abstract
Median bias (eGFR minus mGFR)
EKFC
−4.80
median · 95% CI −7.49–-2.92 · mL/min
- Non-indexed EKFC equation exhibited the highest median bias
- −4.80 mL/min
Further findings
EKFC median bias by BMI subgroup
mL/min
- Overweight
- −7.81 (95% CI −12.87 to −4.80)
- Obesity
- −4.57 (95% CI −8.57 to −1.72)
- Healthy BMI
- −2.50 (95% CI −6.85 to 2.23)
CKD stage classification
- EKFC least accurate for CKD stage classification in patients with obesity, particularly those with hyperfiltration
Original publication
Assessment of GFR Estimation Methods in Patients With Obesity. J Clin Endocrinol Metab. Published 11 September 2025. doi:10.
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