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Computed Tomography Scan Rates and Outcomes in Children Risk-Stratified Using the PREDICT Guideline Algorithm for
Stephen J C Hearps1,2, Emma Tavender1,2,3, Meredith L Borland4,5
1Emergency Research, Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia.
Insights
The PREDICT Guideline effectively risk stratifies pediatric head injuries, but two low-risk cases required neurosurgery, highlighting the need for careful clinical judgment in managing mild to moderate head injuries.
Area of Science:
- Pediatric Emergency Medicine
- Clinical Decision Support Systems
- Trauma Management
Background:
- The PREDICT Guideline aids in managing mild to moderate head injuries in children.
- Its implementation across Australia and New Zealand began in 2021.
- Accurate risk stratification is crucial for appropriate patient management.
Purpose of the Study:
- To evaluate the application of the PREDICT Guideline's risk stratification algorithm.
- To analyze the outcomes of pediatric head injury patients based on guideline-defined risk categories.
Main Methods:
- Secondary analysis of a prospective, multicenter dataset of pediatric head injury patients.
- Stratification of patients into high, intermediate, low, and very low risk categories.
- Calculation of computed tomography (CT) scan rates, abnormal CT rates, and clinically important traumatic brain injury (ciTBI) rates within each risk group.
Main Results:
- Of 18,290 stratified patients, 2.9% were high risk, 26.0% intermediate, 11.5% low, and 57.9% very low risk.
- High-risk group: 59.2% CT rate, 42.1% abnormal CT rate, 8.9% ciTBI rate.
- Very low-risk group: 1.8% CT rate, 0.01% ciTBI rate; 2 patients required neurosurgery.
Conclusions:
- The PREDICT Guideline algorithm successfully stratifies pediatric head injury patients by risk.
- While effective, the guideline's application identified two instances where lower-risk patients experienced ciTBI requiring neurosurgery.
Objective:
Since 2021, the PREDICT Guideline for Mild to Moderate Head Injuries in Children has been widely implemented across Australia and New Zealand. We set out to describe the application of the guideline's risk stratification using an existing database.
Methods:
Secondary analysis of a large multicentre prospective data set of paediatric patients with head injuries. We stratified the sample into high, intermediate, low, and very low risk categories per the PREDICT Guideline algorithm. Rates and 95% confidence intervals (CI) of computed tomography (CT), abnormal CT, and clinically important traumatic brain injury (ciTBI) were determined within these categories.
Results:
Of 20,137 patients, 1847 were excluded from risk stratification as requiring immediate CT scans (GCS ≤ 13) or as special conditions. 18,290 (90.8%) were stratified into risk categories: 542 (2.9%) high, 4843 (26.0%) intermediate, 2138 (11.5%) low, and 10,767 (57.9%) very low. CT rates were 59.2% (95% CI 55.0%-63.4%) and 18.9% (17.8%-20.1%) in high and intermediate risk groups, with subsequent abnormal CT rates of 42.1% (95% CI 36.6%-47.7%) and 17.6% (95% CI 15.1%-20.2%), and ciTBI rates of 8.9% (95% CI 6.6%-11.6%) and 1.3% (95% CI 1.0%-1.6%), respectively. CT rates were 7.1% (95% CI 6.1%-8.3%) and 1.8% (95% CI 1.6%-2.1%) for low and very low risk groups, with ciTBI rates of 0.4% (95% CI 0.2%-0.8%) and 0.01% (95% CI 0.0002%-0.1%). 9 low and 1 very low risk patient had a ciTBI (2 required neurosurgery).
Conclusions:
The PREDICT Guideline algorithm risk stratifies head injuries into high, intermediate, low, and very low risk patients. Two of the missed lower risk patients required neurosurgery.
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