The Efficiency of Focused Assessment with Sonography for Trauma in Pediatric Patients with Blunt Torso Trauma

Abstract

Abstract Introduction: Focused Assessment with Sonography for Trauma (FAST) has attracted attention for its use in the detection of intra-abdominal pathology for pediatric patients. However, computed tomography (CT) remains the gold standard for the assessment of blunt torso trauma. The study examines the effectiveness of FAST both in the detection of intra-abdominal pathology in pediatric patients (<19 years) with blunt torso trauma and in the determination of the need for CT for further examination. Methods: The study was designed as a retrospective observational investigation of diagnostic value. The pediatric patients who were admitted to the Emergency Department with blunt torso trauma between January 2013 and October 2016 were included in the study. The sample of the study comprised 255 patients who met the inclusion criteria. The primary outcome was the effectiveness of FAST in the detection of intra-abdominal pathology and the determination of the need for CT. The secondary outcome was to identify the agreement between CT and FAST for intra-abdominal injuries. The Chi-square test and Fisher’s exact test were used for comparisons. A logistic regression model was developed to determine the variables that independently affect the agreement between FAST and CT. Results: FAST was determined to have low sensitivity (20.3%) despite its high specificity (87%). However; FAST had a good negative likelihood ratio. There was a poor agreement between CT and FAST in terms of the presence of both intra-abdominal and intrathoracic injuries in pediatric patients with blunt trunk trauma. The error rate of FAST increased by five-fold, especially in the presence of concomitant thorax trauma. However, FAST had a good negative likelihood ratio. Conclusion: FAST should not be regarded as an equivalent tool to CT for pediatric patients with blunt torso trauma. It is, instead, a noteworthy complementary tool that is a negative predictor.