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Child Abuse Negl ; 103: 104396, 2020 05.
Article in English | MEDLINE | ID: mdl-32135374

ABSTRACT

BACKGROUND: Knowledge of fracture characteristics among children with medical conditions affecting bone could help to distinguish medical causes from child abuse. OBJECTIVE: Characterize long bone fracture morphology among children diagnosed with medical conditions linked to bone health. PARTICIPANTS AND SETTING: Patients <18 years at a single pediatric hospital diagnosed with a medical condition linked to bone health and ≥1 long bone fracture were studied. METHODS: This retrospective medical record review categorized underlying medical diagnoses as: metabolic bone disease, genetic disorder of connective tissue, neurologic disorder and other chronic disease. A pediatric radiologist reviewed plain films to determine fracture type and location. Descriptive statistics, as well as logistic regression were used to compare fracture types by clinical characteristics. RESULTS: Ninety-four patients were included and their diagnoses were genetic connective disorder (19; 20.2 %), metabolic bone disease (16; 17.0 %), neurologic disorder (27; 28.7 %), and other (32; 34.0 %). A total of 216 long bone fractures were sustained; 52.1 % of children had >1 long bone fracture. Of the 216 fractures, 55 (25.5 %) were in children < 1 year, 118 (54.6 %) were associated with known trauma, and 122 (56.5 %) were in non-ambulatory patients. Lower extremity fractures occurred with greatest frequency and most fractures occurred at the mid-diaphysis. Transverse was the most common fracture type in all diagnostic categories. Children with metabolic disorders had highest odds of transverse fracture (COR 3.55, CI 1.45-8.67; neurologic disorders as reference group). CONCLUSIONS: Diseases affecting bone health can influence fracture morphology. Transverse fractures were most common in bones impacted by disease.


Subject(s)
Bone Diseases/complications , Child Abuse , Fractures, Bone/etiology , Adolescent , Bone Density , Child , Child Abuse/statistics & numerical data , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Logistic Models , Male , Medical Records , Radiography , Retrospective Studies
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