INTRODUCTION: Little information is available regarding the evaluation of renal volume in healthy Latin-American children of different ages. The objective of this work was to establish a predictive model of renal size (volume and length) and develop a web-based calculator. MATERIALS AND METHODS: A selective and representative sample was obtained randomly from the database of healthy children living in Resistencia city, Chaco, Argentina: a) the National Health Program for children under 6 years old; b) school children until 18 years old (primary and middle education). Renal dimensions were obtained by ultrasonography via a single experienced operator at the indicated site (schools or primary health care centers). Renal volume was calculated using Dinkel's formula. A multiple linear regression model was applied using potential predictors. The final model was implemented in a free web-based application. RESULTS: Random selection was made from the database to include 882 subjects with ages between 0.03 and 230.63 months. The data was divided into two sets (one for training and the other for model testing). The training set (423) included 212 (50%) females. Significant predictors included age, height, current weight and birth weight, and the interaction between age and present weight. Using the test dataset, both renal volume and length root mean square errors were 5.06 cm3 and 0.59 cm. CONCLUSION: The prediction model was accurate and allowed for the development a freely-available web app: Renal size prediction (https://porbm28.shinyapps.io/RenalVolume/). Once the models are validated by additional studies, the app could be a useful tool to predict renal volume and length in pediatric clinical practice.
INTRODUCTION: Little information is available regarding the evaluation of renal volume in healthy Latin-American children of different ages. The objective of this work was to establish a predictive model of renal size (volume and length) and develop a web-based calculator. MATERIALS AND METHODS: A selective and representative sample was obtained randomly from the database of healthy children living in Resistencia city, Chaco, Argentina: a) the National Health Program for children under 6 years old; b) school children until 18 years old (primary and middle education). Renal dimensions were obtained by ultrasonography via a single experienced operator at the indicated site (schools or primary health care centers). Renal volume was calculated using Dinkel's formula. A multiple linear regression model was applied using potential predictors. The final model was implemented in a free web-based application. RESULTS: Random selection was made from the database to include 882 subjects with ages between 0.03 and 230.63 months. The data was divided into two sets (one for training and the other for model testing). The training set (423) included 212 (50%) females. Significant predictors included age, height, current weight and birth weight, and the interaction between age and present weight. Using the test dataset, both renal volume and length root mean square errors were 5.06 cm3 and 0.59 cm. CONCLUSION: The prediction model was accurate and allowed for the development a freely-available web app: Renal size prediction (https://porbm28.shinyapps.io/RenalVolume/). Once the models are validated by additional studies, the app could be a useful tool to predict renal volume and length in pediatric clinical practice.
Authors: Laura Torres-Canchala; Martin Rengifo; Guido Filler; Juan C Arias; Oscar Ramirez; Jaime M Restrepo Journal: Pediatr Nephrol Date: 2021-01-07 Impact factor: 3.714