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Factors affecting patients' decision-making and the development of a prognostic model in total knee replacement surgery

Osteoarthritis of the knee is a common condition, affecting more than 10% of the population aged over 55 years. It can lead to pain, functional loss, and a reduction in the quality of life. Total knee replacement is a common procedure for those with severe osteoarthritis with over 90,000 procedures performed each year in the UK; however, around 20% of patients are dissatisfied with the outcome. How to identify these patients pre-operatively is a research priority, as set out by the British Orthopaedic Association, Arthritis Research U.K., and the National Institute for Health and Care Excellence. The effect such an advance would have on patients’ decision-making is not known. Therefore, in this thesis I set out to understand the factors important to patients when contemplating a knee replacement, how an outcome prediction tool could affect that process, and then go on to develop an prognostic model for use in patients considering a total knee replacement. I first performed a systematic review of factors that influence patient’s decision-making; I then describe two qualitative projects, the first developed a model of decision-making, the second investigated how providing predictions of outcome could affect expectations and decision-making. This information, combined with a systematic review of the factors that affect outcome in knee replacements, allowed me to develop a multicentre cohort study designed to generate a prognostic model. This study recruited 600 patients, and the linear regression model accounts for 36% of the variability in outcome – more than any previous study. This thesis provides a better understanding of patients’ decision-making, which should facilitate doctor-patient communication. I describe a model that can predict more variability in outcome than any previous models. The usefulness of the model in individual prediction and potential future areas of study include how more variability could be incorporated, how to develop such a model into a prediction tool, and other approaches to addressing poor outcomes after total knee replacement.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:704104
Date January 2016
CreatorsBarlow, Timothy
PublisherUniversity of Warwick
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://wrap.warwick.ac.uk/86003/

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