Shiny and Mobile Apps for Estimating Blood Pressure Percentiles in Children
Shiny and Mobile Apps for Estimating Blood Pressure Percentiles in Children

Shiny and Mobile Apps for Estimating Blood Pressure Percentiles in Children

Hypertension. 2025 Oct 1. doi: 10.1161/HYPERTENSIONAHA.125.25087. Online ahead of print.

ABSTRACT

BACKGROUND: The American Academy of Pediatrics, the European Society of Hypertension, and the European Society of Cardiology propose distinct hypertension classification criteria for children and adolescents based on 2 percentile derivations and different fixed blood pressure thresholds at different ages, leading to potential confusion in clinical and research settings.

METHODS: We developed 2 Shiny apps and 1 mobile app that allow simultaneous calculation of blood pressure percentiles using both methods and classify hypertension according to each guideline. The first Shiny app was designed for research purposes, offering an efficient tool for handling large pediatric data sets. The second Shiny app and the mobile app are designed for clinical use, presenting the same relevant outcomes for individual patients in a user-friendly interface. The research-focused app was tested on 3 data sets varying in age, blood pressure, and weight distributions.

RESULTS: When comparing the 3 hypertension classifications across the samples, the American Academy of Pediatrics and European Society of Cardiology criteria consistently identified more individuals as hypertensive than the European Society of Hypertension across all age and weight groups, resulting in discordance rates from 2.3% to 21.1%. In contrast, the American Academy of Pediatrics and the European Society of Cardiology showed high agreement, with minimal or absent discordance ranging from 0.0% to 4.4%. An exception was seen in ages of 13 to 16 years, where differing criteria led to greater and unpredictable discordance.

CONCLUSIONS: These apps offer researchers and clinicians powerful tools to calculate blood pressure percentiles and hypertension classifications based on different guidelines. This marks an important first step toward identifying which classification best predicts clinical outcomes.

PMID:41031395 | DOI:10.1161/HYPERTENSIONAHA.125.25087