ASN's Mission

ASN leads the fight to prevent, treat, and cure kidney diseases throughout the world by educating health professionals and scientists, advancing research and innovation, communicating new knowledge, and advocating for the highest quality care for patients.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on Twitter

Kidney Week

Abstract: PO2234

A Plasma Creatinine- and Urea-Based Equation to Estimate Glomerular Filtration Rate in Rats

Session Information

Category: Pathology and Lab Medicine

  • 1601 Pathology and Lab Medicine: Basic

Authors

  • Pieters, Tobias, Universitair Medisch Centrum Utrecht, Utrecht, Utrecht, Netherlands
  • Besseling, Paul J., Universitair Medisch Centrum Utrecht, Utrecht, Utrecht, Netherlands
  • Nguyen, Isabel T.N., Universitair Medisch Centrum Utrecht, Utrecht, Utrecht, Netherlands
  • Bree, Petra De, Universitair Medisch Centrum Utrecht, Utrecht, Utrecht, Netherlands
  • Rookmaaker, Maarten B., Universitair Medisch Centrum Utrecht, Utrecht, Utrecht, Netherlands
  • Gerritsen, Karin G., Universitair Medisch Centrum Utrecht, Utrecht, Utrecht, Netherlands
  • Verhaar, Marianne C., Universitair Medisch Centrum Utrecht, Utrecht, Utrecht, Netherlands
  • Gremmels, Hendrik, Universitair Medisch Centrum Utrecht, Utrecht, Utrecht, Netherlands
  • Joles, Jaap A., Universitair Medisch Centrum Utrecht, Utrecht, Utrecht, Netherlands

Group or Team Name

  • Verhaar
Background

Monitoring renal function is a vital part of kidney research involving rats. Measurement of Glomerular Filtration Rate (GFR) with an exogenous filtration marker is laborious and does not easily allow serial measurements. Plasma concentrations of creatinine and urea are often used as surrogate, although their correlation with GFR has not been thoroughly investigated in a large cohort of rats. Goal of this study was to develop an eGFR equation for rats.

Methods

We used an in-house collected database of 691 experiments in male rats with gold-standard GFR measurement (inulin clearance, mGFR) and plasma creatinine, plasma urea, weight, and strain (Lewis, Fawn-Hooded, Sprague-Dawley, Wistar). The equation was derived in a development cohort (n=442) and validated in a validation cohort (n=249). Subsequently, we measured plasma cystatin C in a random subset (n=242) to test its added value to the model.

Results

All parameters that were included during model development correlated to mGFR (weight, R2=0.065; creatinine, R2=0.756; urea, R2=0.633; strain, R2=0.014; all p<0.001). Using linear regression with a piece-wise linear spline for creatinine, we developed the following equations in the development cohort.

Plasma creatinine <48 (µmol/L): eGFR=833*W0.677*C-0.585*U-0.425
Plasma creatinine ≥48 (µmol/L): eGFR=8173*W0.677*C-1.175*U-0.425
eGFR= estimated GFR (µL/min), W= weight (gram), C=creatinine (µmol/L), U=urea (mmol/L).

Subsequent evaluation in the validation cohort yielded similar precision and accuracy (R2=0.872, p30=69%) as in the development cohort (R2=0.801, p30=73%). Inclusion of strain in the model increased neither precision nor accuracy.
Although plasma cystatin C correlated with mGFR (R2=0.242,p<0.001), it did not add predictive power to the model (R2-change=0.0004, p=0.64), and therefore not measured in the entire dataset nor included in the model.

Conclusion

We are the first to develop an equation to estimate GFR in male rats. This equation allows a less labour intensive and invasive repetitive estimation of GFR in rats, and may reduce experimental animal numbers. Validation in an external cohort, in females, and in other disease models is required.