Kidney Week

Abstract: TH-PO731

Race Independent eGFR Equations in Assessing Renal Function in Patients With Liver Disease

Session Information

• Diversity and Equity in Kidney Health - I
  November 03, 2022 | Location: Exhibit Hall, Orange County Convention Center‚ West Building
  Abstract Time: 10:00 AM - 12:00 PM

Category: Diversity and Equity in Kidney Health

• 800 Diversity and Equity in Kidney Health

Authors

• Meeusen, Jeff W., Mayo Clinic Department of Laboratory Medicine and Pathology, Rochester, Minnesota, United States

Jeff W. Meeusen,

• Dasari, Surendra, Mayo Clinic Department of Laboratory Medicine and Pathology, Rochester, Minnesota, United States

Surendra Dasari,

• Lieske, John C., Mayo Clinic Department of Laboratory Medicine and Pathology, Rochester, Minnesota, United States

John C. Lieske,

• Lemoine, Sandrine, Department Néphrologie, Dialyse, Hypertension et Exploration Fonctionnelle Rénale, Groupement Hospitalier Eduard Herriot, Hospices Civiles de Lyon, Université Claude Bernard, Lyon, France

Sandrine Lemoine,

• Dubourg, Laurence, Department Néphrologie, Dialyse, Hypertension et Exploration Fonctionnelle Rénale, Groupement Hospitalier Eduard Herriot, Hospices Civiles de Lyon, Université Claude Bernard, Lyon, France

Laurence Dubourg,

• Stämmler, Frank, Numares AG, Regensburg, Germany

Frank Stämmler,

• Schiffer, Eric, Numares AG, Regensburg, Germany

Eric Schiffer,

Background

Renal impairment is commonly associated with liver disease, and the degree of renal dysfunction impacts decisions regarding drug dosing, therapeutic interventions, and suitability for liver transplantation. Altered hemodynamics in liver disease often result in overestimation of glomerular filtration rate (GFR) by creatinine based GFR estimating equations. Recently, we have analytically and clinically validated a novel GFR estimation equation based on serum myoinositol, valine, and creatinine quantified by nuclear magnetic resonance spectroscopy in combination with cystatin-C, age and sex (AXINON® GFR(NMR)). We hypothesized that AXINON® GFR(NMR) (GFR_NMR) could improve CKD classification in the setting of liver disease.

Methods

We compared GFR estimation equations in a multicenter retrospective study of patients (n=203) with liver disease and renal tracer clearance measured GFR (mGFR). Stored serum was analyzed and used to estimate GFR based on GFR_NMR, CKD-EPI 2021 eGFRcr-cys, and CKD-EPI 2021 eGFRcr.

Results

eGFRcr overestimated mGFR with a mean bias of 7.5 [4.9 - 9.8] mL/min/1.73m² compared to a smaller bias of -2.9 [-4.8 - -1.3] for eGFRcr-cys and -1.64 [-3.43 - 0.16] for GFR_NMR (both p<0.001). P₃₀ was similar in GFR_NMR and eGFRcr-cys (83% [79 - 89] and 86% [81 - 90]) but lower for eGFRcr (74% [68 – 80]). P₁₅ was highest for GFR_NMR at 59% [53 - 65] compared to 47% [40 - 53] for eGFRcr and 54% [47 - 61] for eGFRcr-cys. Concordant classification by mGFR CKD stage was 104 (51%), 109 (54%), and 120 (59%), for eGFRcr, eGFRcr-cys, and GFR_NMR respectively (GFR_NMR vs. eGFRcr: p = 0.074; GFR_NMR vs. eGFRcr-cys: p = 0.138; eGFRcr vs. eGFRcr-cys: p = 0.588).

Conclusion

Our findings confirm that the new 2021 eGFRcr equation overestimates GFR among patients with liver disease, presumably due to reduced muscle mass. Addition of myoinositol and valine improved correlation of GFR_NMR with mGFR and accurately stratified liver disease patients into CKD stages.