• I R Murray, C J Foster, A Eros, and C M Robinson.
• The Edinburgh Shoulder Clinic, The Royal Infirmary of Edinburgh, Little France, Old Dalkeith Road, Edinburgh EH16 4SU, United Kingdom.
• J Bone Joint Surg Am. 2013 Jul 3;95(13):1153-8.

BackgroundIdentification of patients at higher risk of nonunion after diaphyseal clavicular fractures is desirable to improve patient counseling and enable targeted surgical treatment.MethodsSeventy-nine percent (941 of 1196) of diaphyseal clavicular fractures were followed to union or nonunion. Demographic, injury, and radiographic characteristics associated with nonunion were determined with use of bivariate and multivariate statistical analyses.ResultsIn patients who were eighteen years of age or older, 125 (13.3%) of the fractures had clinical and radiographic evidence of nonunion. Factors significantly associated with nonunion on bivariate analysis were sex, smoking status, overall fracture displacement, overlap, translation, and comminution. The factors that maintained significance on multivariate analysis were smoking (odds ratio, 3.76), comminution (odds ratio, 1.75), and fracture displacement (odds ratio, 1.17). If all displaced midshaft fractures were managed operatively, 7.5 procedures would need to be undertaken to prevent a single nonunion. If only fractures with a predicted probability of ≥40% were managed operatively, the number of patients managed operatively to prevent a single nonunion would fall to 1.7.ConclusionsThirteen percent of displaced diaphyseal fractures in patients who were at least eighteen years of age did not heal. Smoking was the strongest risk factor, and smoking cessation should be an integral part of treatment. The probability of nonunion in a particular individual can be estimated with use of a statistical model based on known risk factors. This information can be useful when counseling the patient even though nonunion remains difficult to predict accurately in that individual. The number who would need to be treated to prevent a single nonunion can be reduced by identifying those at higher risk.

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