Naomi T. Nkinsi, MD, MPH, on Racial Bias in Diagnosing Kidney Disease
Why It Matters
Removing race from kidney‑function equations improves diagnostic accuracy and expands timely treatment for Black patients, advancing health equity and reducing systemic bias in care.
Key Takeaways
- •Clinical algorithms embed race, skewing kidney disease diagnosis for Black patients.
- •Racial coefficient delayed CKD detection, limiting transplant and treatment access.
- •Medical trainees increasingly challenge entrenched racial biases in practice.
- •Recent reforms aim to remove race from kidney function equations.
- •Next‑generation clinicians expected to drive equitable diagnostic standards.
Summary
In a recent interview, Dr. Naomi T. Nkinsi, MD, MPH, highlighted how racial bias is embedded in clinical algorithms used to diagnose kidney disease in the United States.
She explained that the historic use of a race‑based coefficient in estimated glomerular filtration rate (eGFR) calculations caused Black patients to be classified with higher kidney function than they actually had, postponing chronic kidney disease (CKD) diagnosis and limiting eligibility for early interventions such as dialysis planning and transplantation.
Nkinsi noted, “One of the more insidious forms of racism is the ways in which racial coefficients…lead to Black patients getting diagnosed later.” She praised the growing vocal opposition from trainees and clinicians who are pushing to eliminate race from these equations.
The shift away from race‑adjusted formulas promises more accurate detection, earlier treatment, and a step toward dismantling systemic inequities in nephrology, signaling a broader movement for equity across medical practice.
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