#4145 ACLARA: AN ON-LINE CALCULATOR TO ESTIMATE CREATININE CLEARANCE IN RATS
Authors: Fuentes-Calvo Isabel , Alonso Eva María Baranda , Diaz-Morales Noelia , Pellicer-Valero Óscar , Massaro Giampiero A , Casanova Alfredo G , Sancho María Paniagua , Harvat Mykola , Martín José D , Salgado Carlos Martinez , Lopez-Hernandez Francisco J 
Published: June 2023

Background and Aims

Creatinine clearance (ClCr) is a standard method for the measurement of glomerular filtration rate in rats. Recently, we developed ACLARA, an open and freely available neural network (NN)-based calculator of ClCr in Wistar rats (http://idal.uv.es/aclara). By working solely on plasma creatinine concentration and body weight, ACLARA instantly and easily provides accurate ClCr estimations with an identical concept to that underlying human glomerular filtration rate (GFR)-estimating formulae utility in the clinical setting. In addition to saving costs and time, ACLARA aligns with the 3Rs principles by providing a methodological refinement tool that reduces experimental animal stress derived from avoiding confinement in metabolic cages for individual, 24-hour urine collection. As a potential limitation, ACLARA was developed with data from Wistar rats. Accordingly, the aim of this study is to study ACLARA's accuracy and utility in a different rat strain, namely the spontaneous hypertensive rat (SHR).

Method

In order to further validate the calculator, we used a dataset with 1,458 entries from unpublished experiments of AKI induced in Wistar and SHR male rats. Measured ClCr (mClCr) was determined with a standard procedure, as we previously described [1], and estimated ClCr (eClCr) was calculated using ACLARA. Calculator performance was assessed with the mean absolute error (MAE) and the Pearson product-moment correlation coefficient calculated as previously described [2]. Results of eCLCr were compared with their corresponding mClCr values in the context of individual experiments.

Results

Our study reveals that ACLARA performs with reasonably high accuracy at ClCr estimation in both Wistar and SHR rats as indicated by Pearson's product-moment correlation coefficient (Corr) and MAE. The global Corr for the 1,458 measured versus estimated data values reaches 0.9, and a MAE of 0.18 mL/min. In general, estimated data provide identical results to measured data for individual experiments considered in the whole and, if anything, depict more congruent behavior. We interpret this improvement as the consequence of bypassing experimental errors introduced by the well-known discrepancies between the real and measured urinary flow in metabolic cages. Interestingly, ACLARA performs with accuracy through the range of ages and for all experimental conditions tested, including pharmacological treatments. Figure 1 shows a representative experiment in which measured and estimated data are compared holistically.

Conclusion

ACLARA is an easy-to-use and reliable tool to estimate creatinine clearance in SHR and Wistar rats from plasma creatinine concentration and body weight data. Validation for a second rat strain suggests a potential, wider application of ACLARA through laboratory rats, which needs to be further studied. In this sense, collaboration and use by independent investigators and recruitment of additional data sets from other laboratories is strongly sought to further adjust the calculator in order to enhance its accuracy, extend its applicability and improve its utility to the scientific community. This study was supported by Project PI21/01226, funded by Instituto de Salud Carlos III (ISCIII) and co-funded by the European Union, and a grant from the Consejería de Educación, Junta de Castilla y León (IES160P20), Spain, co-funded by FEDER funds; and a grant from the Valencian Government with reference number CIAICO/2021/184. Noelia Diaz-Morales is recipient of a Juan de la Cierva-Formación postdoctoral contract (FJC2020-043205-I) funded by MCIN/AEI/10.13039/501100011033 and European Union “NextGenerationEU/PRTR”.