JMIR Publications

ABSTRACT

Background:

Traumatic brain injuries (TBIs) and intra-abdominal injuries (IAIs) are two leading causes of traumatic death and disability in children. To avoid missed or delayed diagnoses leading to increased morbidity, computed tomography (CT) is used liberally. However, overuse of CT leads to inefficient care and radiation-induced malignancies. Therefore, to maximize precision and minimize overuse of CT, the Pediatric Emergency Care Applied Research Network (PECARN) previously derived clinical prediction rules for identifying children at high risk and very low risk for IAIs undergoing acute intervention and clinically important TBIs after blunt trauma in large cohorts of injured children.

Objective:

The objective of this study was to validate the IAI and age-based TBI clinical prediction rules for identifying children at high risk and very low risk for IAIs undergoing acute intervention and clinically important TBIs after blunt trauma.

Methods:

This study was a prospective six-center observational study of children <18 years with blunt torso or head trauma. Consistent with the original derivation studies, enrolled children underwent routine history and physical examinations, and the treating clinician completed a case report form prior to knowledge of CT results (if performed). Medical records were reviewed to determine clinical courses and outcomes for all patients and, for those who were discharged from the Emergency Department (ED), a follow-up survey via a telephone call or text was performed to identify any patients with missed IAIs or TBIs. The primary outcomes were IAI undergoing acute intervention (therapeutic laparotomy, angiographic embolization, blood transfusion, or intravenous fluid for ≥ 2 days for pancreatic/gastrointestinal injuries) and clinically-important TBI (death from TBI, neurosurgical procedure, intubation for > 24 hours for TBI, or hospital admission of ≥ 2 nights due to a TBI on CT). Prediction rule accuracy was assessed by measuring rule classification performance, using standard point interval estimates with 95% confidence interval estimates of sensitivity, specificity, positive (PPV) and negative (NPV) predictive values and diagnostic likelihood ratios of each prediction rules’ test characteristics (sensitivity, specificity, PPV, NPV, and diagnostic likelihood ratios.)

Results:

The project was funded in 2016 and enrollment was completed in August 2021. Data analyses are underway, and results are expected to be submitted for publication in 2022.

Conclusions:

This study will attempt to validate previously derived clinical prediction rules to accurately identify children at high and very low risk for important IAIs and TBIs. Assuming successful validation, widespread implementation is then indicated which will optimize care of injured children by better aligning CT use with need.