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Validation of the Predictive Model for Operative Intervention Afterblunt Abdominal Trauma in Children Withequivocal Ct Findings: A Multi-institutional Study
Abdulraouf Lamoshi1, Raymond Lay2, Derek Wakeman2, Mary Edwards3, Kim Wallenstein4, Tiffany Fabiano5, Zorawar Singh3, Jacob Zipkin3, Soyun Park6, Jihnhee Yu6, Mitchell Chess7, Vali Kaveh8
1Cohen Children's Medical Center, New Hyde Park, NY; 2University of Rochester, Rochester, NY; 3Albany Medical College and Center, Albany, NY; 4Upstate Medical University, Syracuse, NY; 5John R. Oishei Children's Hospital, Buffalo, NY; 6University at Buffalo, Buffalo, NY; 7University of Rochester Medical Center, Rochester, NY; 8John R. Oishei Children's Hospital, Buffalo, NY

Background: We recently developed a preliminary predictive model identifying clinical and radiologic factors associated with the need for surgery following blunt abdominal trauma (BAT) in children. Our aim in this study was to further validate the factors in this predictive model in a multi-institutional stud
Methods: A retrospective chart review of pediatric patients from five pediatric trauma centers who experienced BAT between 2011 to 2020 was performed. Patients under 18 years of age who had BAT, hemodynamically stable, had a CT abdomen, and had no evidence of pneumoperitoneum were included. Fisher’s exact test was used for statistical analysis of the association between the following risk factors and need for laparotomy: Abdominal wall bruising (AWB), Abdominal pain/tenderness (APT), thoracolumbar fracture (TLF), presence of free fluid (FF), presence of solid organ injury (SOI). A predictive logistic regression model was then estimated employing these factors.
Findings: Of 734 patients identified in the multi-institutional dataset as having both BAT and abdominal CT scans ordered, 726 were included. Of those, 59 required surgical intervention (8.8%). Univariate analysis of association between the studied factors and need for surgical management showed that the presence of TLF (p < 0.01), APT (p < 0.01), FF (p < 0.01), and SOI (p < 0.01) were significantly associated. A predictive model was created using the 5 factors, resulting in an Area Under the Curve (AUC) of 0.80. For the MVC group, only FF, SOI, and TLF are significantly associated with the surgical interventions. The AUC for the predictive model for the MVC group was 0.87.
Conclusions: A clinical and radiological prediction rule was validated using a large multi-institutional dataset of pediatric BAT patients, demonstrating a high degree of accuracy in identifying children requiring surgery. FF, SOI, and TLF are the most important factors associated with the need for surgical intervention.


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