Validation of the Pediatric Resuscitation and Trauma Outcome (PRESTO) model in injury patients in Tanzania.

INTRODUCTION: Sub-Saharan Africa has the highest rate of unintentional paediatric injury deaths. The Pediatric Resuscitation and Trauma Outcome (PRESTO) model predicts mortality using patient variables available in low-resource settings: age, systolic blood pressure (SBP), heart rate (HR), oxygen saturation, need for supplemental oxygen (SO) and neurologic status (Alert Verbal Painful Unresponsive (AVPU)). We sought to validate and assess the prognostic performance of PRESTO for paediatric injury patients at a tertiary referral hospital in Northern Tanzania. METHODS: This is a cross-sectional study from a prospective trauma registry from November 2020 to April 2022. We performed exploratory analysis of sociodemographic variables and developed a logistic regression model to predict mortality using R (V.4.1). The logistic regression model was evaluated using area under the receiver operating curve (AUC). RESULTS: 499 patients were enrolled with a median age of 7 years (IQR 3.41-11.18). 65% were boys, and in-hospital mortality was 7.1%. Most were classified as alert on AVPU Scale (n=326, 86%) and had normal SBP (n=351, 98%). Median HR was 107 (IQR 88.5-124). The logistic regression model based on the original PRESTO model revealed that AVPU, HR and SO were statistically significant to predict in-hospital mortality. The model fit to our population revealed AUC=0.81, sensitivity=0.71 and specificity=0.79. CONCLUSION: This is the first validation of a model to predict mortality for paediatric injury patients in Tanzania. Despite the low number of participants, our results show good predictive potential. Further research with a larger injury population should be done to improve the model for our population, such as through calibration.

Duke Scholars

Author Catherine Ann Staton Emergency Medicine

Author Joao Vitor Perez De Souza  

Author Joao Ricardo Nickenig Vissoci Emergency Medicine

Author Blandina Mmbaga Duke Global Health Institute