Development of an outcome prediction tool for patients considering a total knee replacement -the Knee Outcome Prediction Study (KOPS)

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• 作者：Tim Barlow ; Mark Dunbar ; Andrew Sprowson ; Nick Parsons…
• 关键词：Total knee replacement ; Patient factors ; Outcome prediction tool
• 刊名：BMC Musculoskeletal Disorders
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：15
• 期：1
• 全文大小：242 KB
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• 刊物主题：Orthopedics; Rehabilitation; Rheumatology; Sports Medicine; Internal Medicine;
• 出版者：BioMed Central
• ISSN：1471-2474

文摘

Background Knee osteoarthritis affects 10% of the UK population over 55?years, resulting in pain and decreased quality of life. Knee replacement surgery has a proven benefit, with over 85,000 performed each year in the UK; however, approximately 17% of people are dissatisfied after surgery. Consequently, some Primary Care Trusts have reduced the funding available for knee replacements. Most previous work has focused on the effect of different prostheses and treatment protocols on patient’s outcome. However, this has been unable to account for all the variability and there is growing evidence that patient factors may significantly affect outcome. How to identify these at risk patients has been identified as a research priority by the National Institute of Clinical Excellence, the British Orthopedic Association, and the National Joint Registry. The aim of this study is to develop a clinically appropriate outcome prediction tool based on measurable predictors affecting outcome. Methods/design We propose a prospective cohort study, designed to develop and validate an outcome prediction tool based on patient factors. Six hundred patients who are scheduled for total knee replacement secondary to primary osteoarthritis will be recruited before surgery from all six hospitals (NHS and private) that provide total knee replacements to the population of Coventry and Warwickshire (UK). Patients will complete a baseline assessment of patient factors before their operation and will be followed up at 6 and 12?months post surgery. Discussion A clinically appropriate outcome prediction tool will allow patients to make a more informed decision regarding surgery. Aligning patient expectations with a realistic prediction of outcome should improve satisfaction. Ultimately, this project is likely to inform national policy making and regional service provision.