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Predictive Model for Operative Intervention after Blunt Abdominal Trauma in Children with Equivocal CT Findings: A
Abdulraouf Lamoshi1, Nicole Wagner1, Ziqiang Chen2
1Department of Pediatric Surgery, John R. Oishei Children's Hospital, Buffalo, New York.
Insights
Clinical factors like abdominal wall bruising and tenderness, along with free fluid on CT scans, help predict surgical intervention needs in children with blunt abdominal trauma and unclear CT results.
Area of Science:
- Pediatric Trauma Surgery
- Diagnostic Imaging in Pediatrics
- Emergency Medicine
Background:
- Blunt abdominal trauma (BAT) in children can present with equivocal findings on computed tomography (CT) scans.
- Accurate prediction of surgical intervention is crucial for optimal patient outcomes.
Purpose of the Study:
- To identify clinical and radiologic factors that predict the need for surgical intervention in pediatric patients with BAT and equivocal CT findings.
- To develop a predictive model for surgical necessity.
Main Methods:
- Retrospective review of a level I pediatric trauma center database (2011-2019).
- Analysis of factors including abdominal wall bruising (AWB), abdominal pain/tenderness (APT), thoracolumbar fracture, free fluid (FF), and solid organ injury.
- Statistical analysis using t-test, Kruskal-Wallis test, and logistic regression.
Main Results:
- Of 61 pediatric patients with BAT and equivocal CT findings, 12 (19.7%) required surgery.
- Surgical intervention was significantly associated with patient age, APT, AWB, and FF.
- A predictive model incorporating these factors achieved a receiver operating characteristic curve of 0.86.
Conclusions:
- Abdominal wall tenderness, AWB, and FF are significant predictors of operative intervention in pediatric BAT with equivocal CT scans.
- A combined clinical and imaging predictive model can enhance certainty in surgical decision-making.
- Further validation on larger, multi-institutional datasets is recommended.
Background:
To study the clinical and radiologic factors predicting the need for surgical intervention after blunt abdominal trauma (BAT) in children with equivocal computed tomography (CT) scan findings.
Methods:
We performed a retrospective review of the trauma database at our level I pediatric trauma center between 2011 and 2019. We selected patients with BAT and equivocal findings for surgical intervention on CT scan. We studied five factors: abdominal wall bruising (AWB), abdominal pain/tenderness (APT), thoracolumbar fracture, the presence of free fluid (FF), and the presence of solid organ injury, all previously reported in the literature to predict the need for operative intervention. We used t-test, the Kruskal-Wallis test and logistic regression to study the association of these factors with the need for operation in our pediatric cohort.
Results:
Of 3044 blunt trauma patients, 288 had abdominal CT scans with 61 patients demonstrating equivocal findings. Operation was performed for 12 patients (19.7%) confirming surgically correctable traumatic injuries. The need for surgical intervention was significantly associated with the age of the patients (P = 0.03), the presence of APT (P = 0.001), AWB (P = 0.01), and FF (P = 0.04). The presence of thoracolumbar fracture and solid organ injury were not significantly associated with the need for operation. For the subset of 37 patients who were injured in a motor vehicle crash, five (13.5%) required surgical intervention, which was significantly associated with the presence of AWB (P = 0.04), APT (P = 0.01), and FF (P = 0.03). A predictive model that used these factors produced a receiver operating characteristic curve of 0.86.
Conclusions:
In cases of equivocal abdominal CT scan findings to evaluate BAT in children, the presence of abdominal wall tenderness, AWB, or FF may be significant factors predicting more accurately the need for operative intervention. A predictive model using the combination of clinical and image findings might determine with more certainty, the need for surgical intervention in children with BAT and equivocal CT findings. Validation on a larger multi-institutional data set should be done.
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