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Abstract: TH-PO733

The Effect of CKD-EPI Race Adjustment on CKD Lab Monitoring Guidelines

Session Information

Category: Diversity and Equity in Kidney Health

  • 800 Diversity and Equity in Kidney Health

Authors

  • Gottlich, Harrison Chase, Mayo Clinic Minnesota, Rochester, Minnesota, United States
  • Giblon, Rachel, Mayo Clinic Minnesota, Rochester, Minnesota, United States
  • Astudillo Potes, Maria, Mayo Clinic Minnesota, Rochester, Minnesota, United States
  • Hickson, LaTonya J., Mayo Clinic Minnesota, Rochester, Minnesota, United States
  • Albright, Robert C., Mayo Clinic Minnesota, Rochester, Minnesota, United States
  • Norby, Suzanne M., Mayo Clinic Minnesota, Rochester, Minnesota, United States
  • Thorsteinsdottir, Bjoerg, Mayo Clinic Minnesota, Rochester, Minnesota, United States
Background

Chronic kidney disease (CKD) affects 1 in 7 Americans with 90% of adults unaware of their disease. Routine lab monitoring is crucial for optimal CKD disease management and to avoid “crashing into dialysis”. Historically, eGFR estimation has used a race adjustment for Black patients, contributing to inequity in CKD care. In this study, we investigated the impact of the race adjustment and other predictors on guideline concordance in a cohort of primary care patients.

Methods

We compiled a dataset of 1,167,056 lab results of 125,415 adults receiving care at 75 mid-west primary care practices in an integrated health system, with at least one creatinine level measured between 2014-2016. Relevant covariates were extracted from the medical chart. We characterized using descriptive statistics and recalculated GFR for self-identified Black patients without race adjustment to observe any changes in CKD stage and lab monitoring. Guideline concordant care was modeled as a binary outcome, and considered positive if patients had the recommended number of labs. Predictors of guideline concordance were examined using generalized additive models with random effects for repeat labs over time.

Results

Without race adjustment, 458 (33%) of Black patients would be reclassified to a higher CKD stage based on GFR alone. We found a significant gap in baseline albuminuria, with only 10% of Black and 29.1% of non-Black patients having albuminuria measures (p<.0001). This prevented proper risk stratification of many Black patients in CKD stage 3-5 (22% without race correction vs. 13% with race correction), representing a gap care for proper management. For predictors of guideline concordance assuming patients without baseline albuminuria had a status of A1, patients identifying as Black (OR: 1.35, 95% CI: 1.21-1.43) or who were diagnosed with Hypertension (OR: 3.29, 95% CI: 3.22-3.54), Diabetes (OR: 1.55, 95% CI: 1.50-1.60), or AKI (OR: 1.96, 95% CI: 1.91-2.00) were more likely to be concordant.

Conclusion

In addition to considering the appropriateness of the race adjustment in the CKD-EPI eGFR calculation, we found disparities exist in routine albuminuria labs, particularly for Black patients. This finding underscores the importance of screening as patients are more likely to reach lab compliance when risk factors are identified.