Mendon Priyanka, Witsch Michael, Becker Marianne, Adamski Aurélie, Vaillant Michel
Competence Centre for Methodology and Statistics, Department of Medical Informatics, Luxembourg Institute of Health, Strassen, Luxembourg.
Pediatric Endocrinology and Diabetology, Centre Hospitalier de Luxembourg, Strassen, Luxembourg.
BMC Med Res Methodol. 2024 Dec 5;24(1):298. doi: 10.1186/s12874-024-02405-0.
Monitoring 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.
Leveraging 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.
Bland-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.
The 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.
通过评估体重、身高和体重指数等人体测量变量来监测身体发育，对于评估儿童的身体发育和营养状况至关重要。这种方法有助于早期识别身体发育障碍，从而能够及时进行医疗干预。传统上它依赖于Z分数，即将人体测量变量与参考标准进行比较。除了身体发育监测外，由于潜在的长期健康风险，儿童和青少年高血压的早期检测和管理也至关重要。然而，手动计算Z分数既耗时又容易出错，阻碍了对高危儿童的及时干预。本文介绍了一种创新的开源解决方案，可在电子数据采集平台Research Electronic Data Capture（REDCap™）中直接进行实时Z分数评估，旨在简化儿童身体发育的监测。
利用世界卫生组织（WHO）的生长标准和国家健康与营养检查调查（NHANES）的参考数据，我们的方法将Z分数计算直接集成到REDCap中，为医疗保健专业人员和研究人员提供了一个安全且用户友好的环境。我们使用布兰德-奥特曼分析方法，将我们的方法与已有的计算器（Knirps和Growth XP™）进行比较，所有变量均使用合成数据值。
布兰德-奥特曼图显示，我们在REDCap中的计算结果与Knirps和Growth XP系统之间具有很强的一致性。身高、体重指数和血压的Z分数始终一致，证实了我们的方法在整个测量范围内的准确性。
与REDCap的集成简化了数据收集和分析，无需单独的软件和数据导出。此外，我们的解决方案使用了世界卫生组织（WHO）的生长标准和国家健康与营养检查调查（NHANES）的参考数据。这不仅确保了计算准确性，还提高了其在不同研究背景下的适用性。布兰德-奥特曼分析确定了我们方法的可靠性，有助于采用更有效的方法来监测儿童生长和血压。
