PreScreen
Online PredictionGriffith University Independent Validation
The PreScreen online estimation model was independently validated by Dr Zang and Professor Ware at Griffith University's Biostatistics Unit.
Study Overview
The validation study compared PreScreen's predicted central systolic blood pressure values against actual clinical measurements obtained from the Uscom BP+ device across 935 data points collected from multiple healthcare settings.
Correlation coefficient between predicted and measured cSBP
Statistical significance of the correlation
Average margin of error across all data points
Methodology
PreScreen uses self-reported biometrics including age, sex, height, weight, and lifestyle factors to estimate central systolic blood pressure. The model was developed using machine learning techniques trained on clinical data from Uscom BP+ measurements.
The Griffith University study confirmed that the model produces clinically meaningful estimates that can identify individuals who may benefit from further clinical assessment through a ProScreen screening or GP consultation.
Note: This validation applies specifically to the PreScreen estimation model. ProScreen uses the TGA-registered, FDA-cleared Uscom BP+ device for direct measurement and does not rely on the PreScreen algorithm.
From estimation to measurement
PreScreen identifies. ProScreen measures. Together, they create a scalable pathway to better cardiovascular health.