Validation of a Prediction Tool for Abusive Head Trauma

Abstract
BACKGROUND AND OBJECTIVES: Abusive head trauma (AHT) may be missed in the clinical setting. Clinical prediction tools are used to reduce variability in practice and inform decision-making. From a systematic review and individual patient data analysis we derived the Predicting Abusive Head Trauma (PredAHT) tool, using multilevel logistic regression to predict likelihood of AHT. This study aims to externally validate the PredAHT tool. METHODS: Consecutive children aged RESULTS: Data included 133 non-AHT cases and 65 AHT cases, 97% of children were CONCLUSIONS: When tested on novel data, the PredAHT tool performed well. This tool has the potential to contribute to decision-making in these challenging cases. An implementation study is needed to explore its performance and utility within the child protection process.