Epidemiological features and injury patterns of multiple fractures in children: a cross-sectional study

儿童多发性骨折的流行病学特征和损伤模式:一项横断面研究

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Abstract

OBJECTIVE: This study aims to evaluate the epidemiological features of multiple pediatric fractures and identify specific injury patterns. METHODS: This cross-sectional study retrospectively analyzed medical records for children with multiple fractures who presented to Children's Hospital of Nanjing Medical University between 2016 and 2024. Fractures were categorized into six anatomical regions: Craniofacial, Trunk/Pelvis, Upper Limb, Lower Limb, Hand, and Foot. Patients were divided into single-region and multi-region groups based on the number of affected regions. Hierarchical clustering on principal components (HCPC) was applied to explore potential injury patterns. RESULTS: Among the 1950 children with multiple fractures, 65.0% were boys, with a median age of 8.7 years (4.8-12.3 years). The primary mechanisms of injury included ground-level falls (36.3%), traffic accidents (13.8%), and play/sports activities (10.8%). Single-region fractures accounted for 77.2%, while multi-region fractures accounted for 22.8%. There were statistically significant differences in age and injury mechanism distributions between the two groups (p < 0.001). In the single-region group, children aged 6-11 years predominated, with ground-level falls being the most common cause (44.4%) primarily resulting in upper limb fractures (74.4%). The multi-region group had a higher representation of adolescents aged 12-17 years, with traffic accidents as the primary cause and injuries mainly involving the lower limbs (63.5%), trunk (56.8%), and upper limbs (50.5%). HCPC identified five distinct injury patterns: Lower Limb-Foot, Trunk/Pelvis-High Fall, Upper Limb-Hand, Craniofacial-Traffic Accident, and Upper Limb-Trunk/Pelvis patterns. CONCLUSION: Most pediatric multiple fractures involve a single anatomical region; however, the burden of cross-regional fractures should not be overlooked. Identifying potential injury patterns is crucial for developing targeted preventive strategies.

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