Back

The distribution of paediatric forearm fractures. A five-year retrospective cohort study of 4,546 forearm fractures in children

Husum, H.-C.; Kold, S.; Rahbek, O.

2025-04-03 orthopedics
10.1101/2025.04.01.25325050 medRxiv
Show abstract

BackgroundForearm fractures are the most common fractures in children, accounting for 41% of all paediatric fractures. Most research focuses on distal forearm fractures, but studies encompassing the entire forearm are limited. This retrospective study describes the distribution and patterns of paediatric forearm fractures over a five-year period. MethodsWe conducted a retrospective cohort study of children aged 0-15 years who received a radiograph of the forearm, wrist or elbow between March 2019 and December 2023 in the study region. Fractures were manually identified and registered from radiological reports. Fracture location, type (complete/incomplete), and epiphyseal involvement were analyzed across different age groups. Statistical analysis was performed using chi-square tests and descriptive statistics. ResultsWe identified 4,547 forearm fractures from 4,291 children. The median age was 10 years, and 57% of the patients were male. Fracture patterns varied significantly across age groups (p<0.001), with older children experiencing more distal, complete, radial, and epiphyseal fractures. Younger children had a higher proportion of incomplete fractures and fewer distal or epiphyseal fractures. No significant differences in Salter-Harris classifications were found between age groups (p=0.69). ConclusionFracture patterns in paediatric forearm fractures vary with age, with older children showing a higher incidence of complete, distal, and epiphyseal fractures. This study provides a detailed characterization of paediatric forearm fractures, which may inform clinical management and preventive strategies, particularly in tailoring age-specific care. Further research should explore the long-term outcomes of these fracture patterns.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.