Journal article

Estimated glomerular filtration rate in children: adapting existing equations for a specific population


Research Areas

Publication Details

Author list: Holness JL, Brink A, Davids MR, Warwick JM

Publisher: Springer Verlag (Germany)

Publication year: 2021

Journal: Pediatric Nephrology

Volume number: 36

Issue number: 3

Start page: 669

End page: 683

Total number of pages: 15

ISSN: 0931-041X

eISSN: 1432-198X

URL: http://dx.doi.org/10.1007/s00467-020-04770-6


Abstract

Background

Creatinine-based glomerular filtration rate (GFR)-estimating equations frequently do not perform well in populations that differ from the development populations in terms of mean GFR, age, pathology, ethnicity, and diet. After first evaluating the performance of existing equations, the aim of this study was to demonstrate the utility of an in-house modification of the equations to better fit a specific population.

Methods

Estimated GFR using 8 creatinine-based equations was first compared to 2-sample 51Cr-ethylenediaminetetra-acetic acid plasma clearance in non-cancer and cancer groups independently. The groups were then divided into development and validation sets. Using the development set data, the Microsoft® Excel SOLVER add-in was used to modify the parameters of 7 equations to better fit the data. Using the validation set data, the performance of the original and modified equations was compared.

Results

Two hundred fifty-six GFR measurements were performed in 160 children. GFR was overestimated in both groups (non-cancer 4.3–22.6 ml/min/1.73 m2, cancer 17.2–46.6 ml/min/1.73 m2). The root mean square error (RMSE) was 19.1–21.8 ml/min/1.73 m2 (non-cancer) and 18.6–20.8 ml/min/1.73 m2 (cancer). The P30 values were 49.1–73.0% (non-cancer) and 19.6–66.0% (cancer). Modifying the parameters of seven equations resulted in significant improvements in the P30 values in the non-cancer (65.0–85.0%) and cancer (79.6–87.8%) groups.

Conclusions

Modifying the parameters of pediatric GFR estimating-equations using a simple Excel-based tool significantly improved their accuracy in both non-cancer and cancer populations.


Projects

Currently no objects available


Keywords

Nuclear Medicine


Last updated on 2021-01-03 at 17:10