New prediction model that uses NJR data could help inform patients of their risks of having shoulder replacement surgery

A new model to predict the risk of serious complications after shoulder replacement surgery that uses NJR data has been developed in a collaboration between researchers from the University of Oxford, University of Bristol, and University of Copenhagen. The model could be an important tool to help both patients and doctors make more informed decisions about this common procedure.

The study, published in The Lancet Rheumatology and funded by the National Institute for Health and Care Research (NIHR) and Herlev and Gentofte Hospital (Denmark), provides patients with personalised estimates of their risk. In collaboration with researchers from the University of Copenhagen and the University of Bristol, the Oxford team used data from the National Joint Registry and NHS Hospital Episode Statistics in England to develop their risk prediction model. They analysed information from over 40,000 shoulder replacement patients, looking at factors such as age and medical conditions.

The research team then externally validated the model on patient data from 6,600 shoulder replacements in Denmark, demonstrating that it performs consistently well and can be applied broadly, beyond just the original English population. ‘We found it was accurate and performed well both in England and Denmark and demonstrated that it has ‘clinical utility’, meaning it is beneficial to use in clinical practice,’ said Epaminondas Markos Valsamis, lead author of the new paper.

‘Despite seeing a year-on-year rise of serious adverse events after shoulder replacement surgery, there is as yet no prediction model in widespread use to provide patients with personalised estimates of their expected risk. Patients, carers and clinicians have previously identified the importance of being able to make accurate predictions of patients outcomes to make well-informed decisions.’

‘Patients need to have realistic expectations about their surgery, and this model helps bridge gaps in their understanding,’ said Gillian Coward, Patient Representative for the National Joint Registry. ‘Armed with their personalised risk information, patients can work closely with their surgeon to decide on the best course of action for their individual circumstances.’

Professor Jonathan Rees, from the Oxford team and Head of the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences explained that the research teams from both England and Denmark are working to develop and make the prediction model widely available online through their national societies and partners.

We will have more news on this soon.

Published paper: https://www.thelancet.com/journals/lanrhe/article/PIIS2665-9913(24)00149-8/fulltext