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Principal Investigator
Dahi Yu
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1 October 2015 to 30 September 2016

Project No: 258

Funding round: FR 9

Musculoskeletal

We are aiming to help doctors predict a patient’s future risk of needing a knee or hip replacement for osteoarthritis. The purpose of this study is to help patients and doctors anticipate the potential need for joint replacement. This could help focus efforts on earlier and more intensive non-surgical treatment that might delay or prevent the need for joint replacement. It may also help with more timely discussion about, and referral for, joint replacement.

 Our study will use information that is routinely collected and recorded in patients’ medical records from a national primary care database – the Clinical Practice Research Datalink. This includes simple information like the age of the patient at the time of diagnosis, whether or not they are overweight, or they have had a serious previous injury to the joint. All of these are known to be risk factors for osteoarthritis getting worse over time but there may be others, such as the strength of painkillers prescribed, the presence of other illnesses, and which part of the country the patient lives. Our study will look across a wide range of factors and work out which ones, used in combination, are the best at predicting joint replacement. The information is anonymised (patients cannot be identified from the data).

 Similar types of risk prediction tools have been developed and are regularly used by doctors and their patients for predicting future risk of heart attacks, stroke, and fractures. We think this would be the first study to try and apply these methods to the prediction of joint replacement.