Development of a radiographic rule in trauma to clinically predict mandibular fractures

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Original Article

Author Details : Admaja K. Nair, Valsa Thomas, Tinky Bose C, Sunu Ramachandran

Volume : 2, Issue : 4, Year : 2016

Article Page : 248-252

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Abstract

Objective: To develop a clinical decision rule with high diagnostic accuracy to detect mandibular fractures in the oral medicine emergency clinic of a tertiary referral centre.
Methodology: A cross sectional study was conducted among 250 trauma patients suspected of mandibular fracture in the oral medicine emergency clinic. Clinical symptoms and signs were recorded in a predesigned proforma. Clinical diagnosis was compared with the gold standard of radiographic diagnosis. Forward step wise logistic regression and recursive partitioning were performed with statistically significant variables, to identify relevant predictors for tool development. It was further refined to develop a maximally sensitive clinical decision rule.
Results: Among the total 250 patients, most common age group for mandibular trauma was 21- 30 years with male to female ratio of 3.4:1. Most common cause of facial trauma was road traffic accidents (RTA). 122 of 250 suspected patients had radiographic evidence of fracture. Condylar fractures were most common. Based on forward step wise logistic regression and recursive partitioning step defect, deranged occlusion, sublingual hematoma and crepitus were identified significant of mandible fracure.The rule RRT Mn# (Radiographic Rule in Trauma- Mandibular Fracture) was developed after recoding each case based on the criteria ‘presence of any of the 4 significant variables’ which improved the diagnostic accuracy to 96.4%.
Conclusion: RRT Mn# is a simple decision rule with high diagnostic precision that can guide in the clinical diagnosis of fracture mandible.

Keywords: Clinical decision rule, Mandible fracture, Diagnostic accuracy, Facial trauma

How to cite : Nair A K, Thomas V, Tinky Bose C, Ramachandran S, Development of a radiographic rule in trauma to clinically predict mandibular fractures. Int J Oral Health Dent 2016;2(4):248-252

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