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Emerg Med J ; 24(10): 707-9, 2007 Oct.
Article in English | MEDLINE | ID: mdl-17901272

ABSTRACT

BACKGROUND: To perform a risk analysis study to determine the probability of a spinal fracture being of malignant origin in patients presenting at a level I trauma centre emergency room after trauma. PATIENTS AND METHODS: Data from 334 consecutive patients were retrospectively obtained from 1993 to 2003. They were divided into two groups: group 1--(benign) traumatic fractures; and group 2--malignant fractures (n = 32). For statistical analysis independent Student t test, chi2 test, and backward-stepwise logistic regression were used. RESULTS: The risk of vertebral fractures appearing to be of malignant origin increased with anatomical location (non-cervical--that is, thoracic or lumbar: odds ratio (OR) 48, 95% confidence interval (CI) 8 to 291), a history of malignancy (OR 72, 95% CI 12 to 422), trauma mechanism (that is, high energy: OR 0.03, 95% CI 0.003 to 0.28), and age >64 years (OR 3, 95% CI 0.9 to 12). Hence, patients over 64 years old attending the emergency room, with a vertebral fracture after a low energy trauma, had an approximately 50% chance of having a malignant fracture. With a non-cervical location and a history of malignancy this increased to 98%. Regardless of the trauma mechanism and age of the patient, a history of a malignancy and a non-cervical fracture posed at least a 36% risk of having a malignant fracture. CONCLUSION: Supported by the present results we feel the probability of malignant fractures, although not frequently encountered, should always be considered in elderly and middle-aged patients with a history of malignancy and a non-cervical traumatic fracture.


Subject(s)
Bone Neoplasms/epidemiology , Emergency Service, Hospital/statistics & numerical data , Fractures, Spontaneous/epidemiology , Spinal Fractures/epidemiology , Accidental Falls/statistics & numerical data , Accidents, Traffic/statistics & numerical data , Adult , Age Distribution , Case-Control Studies , Causality , Comorbidity , Female , Humans , Logistic Models , Male , Middle Aged , Netherlands/epidemiology , Prevalence , Retrospective Studies , Risk Factors , Sex Distribution
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