| Summary: | The studies in the thesis are divided into two broad sections. The first section is descriptive. Data were collected prospectively over a five-and-one-half year period for approximately 4000 fractures. Validation of the data is performed. The data are used to describe the epidemiology of the fracture in the Lothian Region, and the anatomical outcome of the fracture. Multiple logistic regression analysis of the data is performed to identify those factors (recordable at patient presentation) that are prognostic of outcome. The statistical method used provides weighted significance for each of these factors, and thus mathematical formulae predictive of outcomes are constructable. A number of formulae are produced, depending on the displacement of the fracture at presentation (minimally displaced or displaced), and on the outcome measure (early and late instability, the risk of malunion, and carpal malalignment). The second section is validative. The studies in this section are an assessment of the performance of the mathematical formulae in the clinical setting. In the first study, data are collected prospectively for 139 patients, and outcomes recorded. In the second study, a group of clinicians involved in fracture management are asked to predict fracture outcome using first clinical experience and then the predictive formula. Results. The distal radius fracture occurred predominately in the older female patient following a simple fall. The fracture in this typical patient was usually unstable. The most consistently important predictors of fracture outcome were patient age, fracture displacement, comminution and ulnar variance. The mathematical formulae were able to correctly predict anatomical outcome in approximately 7/10 patients in the validative study. This was a significant improvement upon the predictive accuracy of the clinicians using experience alone. Use of the predictive formula also significantly reduced inter-observer variation in the assessment of fracture stability. Conclusion. Use of the predictive formula in the Accident and Emergency setting could improve decision-making in fracture management. By promoting an assessment of fracture stability rather than fracture displacement, appropriate management choices are facilitated. The unstable fracture can be referred for operative management, an ineffective closed reduction avoided. The thesis also demonstrates the potential value of the method employed. Multiple logistic regression analysis may provide a guide to treatment where the management of the condition is dependent upon the natural history.
|
|---|
