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Renal length and volume prediction in healthy children
Insights
This study developed an accurate prediction model for renal volume and length in healthy children, creating a free web app for clinical use. The model utilizes age, height, and weight to estimate kidney size in pediatric patients.
Area of Science:
- Pediatric Nephrology
- Biostatistics
- Medical Imaging
Background:
- Limited data exists on renal volume evaluation in healthy Latin-American children.
- Accurate assessment of renal size is crucial for pediatric health monitoring.
Purpose of the Study:
- To establish a predictive model for renal size (volume and length) in healthy children.
- To develop a user-friendly, web-based calculator for renal size prediction.
Main Methods:
- A random sample of 882 healthy children (0.03-230.63 months) from Argentina was analyzed.
- Renal dimensions were measured using ultrasonography and Dinkel's formula for volume.
- A multiple linear regression model incorporated age, height, weight, and their interactions.
Main Results:
- The predictive model identified age, height, current weight, birth weight, and age-weight interaction as significant predictors.
- The model demonstrated high accuracy with root mean square errors of 5.06 cm³ for volume and 0.59 cm for length.
- A free web application was developed based on the validated prediction model.
Conclusions:
- The developed prediction model is accurate for estimating renal volume and length in children.
- The freely available web application can serve as a valuable tool in pediatric clinical practice.
- Further validation studies are recommended to broaden the applicability of the prediction model.
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.
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