ArticleBMC medical research methodology2024
Facilitating comprehensive child health monitoring within REDCap - an open-source code for real-time Z-score assessments.
Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
Abstract
backgroundMonitoring of somatic development through the assessment of anthropometric variables such as weight, height, and BMI is vital for evaluating the physical development and nutritional status of children. This approach aids in the early identification of somatic developmental disorders, enabling timely medical interventions. It traditionally relies on Z-scores, which compare anthropometric variables with reference standards. In addition to somatic development monitoring, the early detection and management of pediatric and adolescent hypertension are crucial due to potential long-term health risks. However, manual calculations of Z-scores are time-consuming and error-prone, impeding timely interventions for at-risk children. This article introduces an innovative open-code solution for real-time Z-score assessments directly within the electronic data capture platform, Research Electronic Data Capture, (REDCap™), aiming to streamline the monitoring of somatic development in children.
methodsLeveraging the World Health Organization (WHO) growth standards and National Health and Nutrition Examination Survey (NHANES) references, our approach integrates Z-score computations directly into REDCap, providing a secure and user-friendly environment for healthcare professionals and researchers. We employed Bland-Altman analyses to compare our method with established calculators (Knirps and Growth XP™) using synthetic data values for all variables.
resultsBland-Altman plots demonstrated strong agreement between our REDCap calculations and the Knirps and Growth XP systems. Z-scores for height, BMI, and blood pressure consistently aligned, affirming the accuracy of our approach across the measurement range.
conclusionThe integration with REDCap streamlines data collection and analysis, eliminating the need for separate software and data exports. Moreover, our solution uses the World Health Organization (WHO) growth standards and National Health and Nutrition Examination Survey (NHANES) references. This not only ensures calculation accuracy but also enhances its suitability for diverse research contexts. The Bland-Altman analyses establish the reliability of our method, contributing to a more effective approach to child growth and blood pressure monitoring.
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