Pediatric traumatic brain injury: precision risk assessment models and an online calculator for enhanced patient care.

BACKGROUND

Traumatic brain injury (TBI) is a significant public health challenge demanding extensive medical resources. Accurate, individualized risk assessments for extended length of stay (LOS), non-routine discharge, ICU/OR transfers, and direct ED discharges are crucial for optimizing patient care, prompting the authors to develop a reliable risk stratification tool to support clinicians and multidisciplinary care teams.

METHODS

A retrospective review of electronic health records was conducted to identify pediatric TBI cases (age ≤18) using ICD-10 codes based on the modified CDC framework. Data on demographics, neighborhood socioeconomic disadvantage (assessed using the Social Deprivation Index [SDI]), and injury severity (assessed using Injury Severity Scores [ISS]) were collected. The backward elimination method was employed in the multivariate regression analysis to achieve the most parsimonious model. Model discrimination and calibration were assessed using the area under the receiver operating characteristic curve (AUC) and Spiegelhalter's z-test, respectively.

RESULTS

A total of 2954 TBI cases were identified with an average age of 7.05 years. Of these, 28.4 % had extended LOS, 8.3 % had a non-routine discharge, 23.4 % required ICU/OR transfer, and 52.3 % were discharged directly from the ED; respective predictive models achieved AUCs of 0.89, 0.87, 0.89, and 0.88, demonstrating good discrimination. All the referenced models had a Spiegelhalter z-test p-value greater than 0.05, indicating an adequate fit. All models were used to develop an open-access online calculator available at: https://jhpedsnsgy.shinyapps.io/JHPedsNSGY/.

CONCLUSIONS

By integrating readily accessible data in the ED, these predictive models and the online calculator empower clinicians to deliver precise, individualized risk assessments, enhance neurosurgical decision-making, and improve high-value care for pediatric TBI patients.