Comparison of the Pediatric Resuscitation and Trauma Outcome (PRESTO) Model and Pediatric Trauma Scoring Systems in a Middle-Income Country.

Background: The pediatric resuscitation and trauma outcome (PRESTO) model was developed to aid comparisons of risk-adjusted mortality after injury in low- and middle-income countries (LMICs). We sought to validate PRESTO using data from a middle-income country (MIC) trauma registry and compare its performance to the Pediatric Trauma Score (PTS), Revised Trauma Score, and pediatric age-adjusted shock index (SIPA). Methods: We included children (age < 15 years) admitted to a single trauma center in South Africa from December 2012 to January 2019. We excluded patients missing variables necessary for the PRESTO model—age, systolic blood pressure, pulse, oxygen saturation, neurologic status, and airway support. Trauma scores were assigned retrospectively. PRESTO's previously high-income country (HIC)-validated optimal threshold was compared to MIC-validated threshold using area under the receiver operating characteristic curves (AUROC). Prediction of in-hospital death using trauma scoring systems was compared using ROC analysis. Results: Of 1160 injured children, 988 (85%) had complete data for calculation of PRESTO. Median age was 7 (IQR: 4, 11), and 67% were male. Mortality was 2% (n = 23). Mean predicted mortality was 0.5% (range 0–25.7%, AUROC 0.93). Using the HIC-validated threshold, PRESTO had a sensitivity of 26.1% and a specificity of 99.7%. The MIC threshold showed a sensitivity of 82.6% and specificity of 89.4%. The MIC threshold yielded superior discrimination (AUROC 0.86 [CI 0.78, 0.94]) compared to the previously established HIC threshold (0.63 [CI 0.54, 0.72], p < 0.0001). PRESTO showed superior prediction of in-hospital death compared to PTS and SIPA (all p < 0.01). Conclusion: PRESTO can be applied in MIC settings and discriminates between children at risk for in-hospital death following trauma. Further research should clarify optimal decision thresholds for quality improvement and benchmarking in LMIC settings. [ABSTRACT FROM AUTHOR]