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Bone & Joint Open
Vol. 3, Issue 10 | Pages 786 - 794
12 Oct 2022
Harrison CJ Plummer OR Dawson J Jenkinson C Hunt A Rodrigues JN

Aims. The aim of this study was to develop and evaluate machine-learning-based computerized adaptive tests (CATs) for the Oxford Hip Score (OHS), Oxford Knee Score (OKS), Oxford Shoulder Score (OSS), and the Oxford Elbow Score (OES) and its subscales. Methods. We developed CAT algorithms for the OHS, OKS, OSS, overall OES, and each of the OES subscales, using responses to the full-length questionnaires and a machine-learning technique called regression tree learning. The algorithms were evaluated through a series of simulation studies, in which they aimed to predict respondents’ full-length questionnaire scores from only a selection of their item responses. In each case, the total number of items used by the CAT algorithm was recorded and CAT scores were compared to full-length questionnaire scores by mean, SD, score distribution plots, Pearson’s correlation coefficient, intraclass correlation (ICC), and the Bland-Altman method. Differences between CAT scores and full-length questionnaire scores were contextualized through comparison to the instruments’ minimal clinically important difference (MCID). Results. The CAT algorithms accurately estimated 12-item questionnaire scores from between four and nine items. Scores followed a very similar distribution between CAT and full-length assessments, with the mean score difference ranging from 0.03 to 0.26 out of 48 points. Pearson’s correlation coefficient and ICC were 0.98 for each 12-item scale and 0.95 or higher for the OES subscales. In over 95% of cases, a patient’s CAT score was within five points of the full-length questionnaire score for each 12-item questionnaire. Conclusion. Oxford Hip Score, Oxford Knee Score, Oxford Shoulder Score, and Oxford Elbow Score (including separate subscale scores) CATs all markedly reduce the burden of items to be completed without sacrificing score accuracy. Cite this article: Bone Jt Open 2022;3(10):786–794


Bone & Joint Open
Vol. 1, Issue 9 | Pages 576 - 584
18 Sep 2020
Sun Z Liu W Li J Fan C

Post-traumatic elbow stiffness is a disabling condition that remains challenging for upper limb surgeons. Open elbow arthrolysis is commonly used for the treatment of stiff elbow when conservative therapy has failed. Multiple questions commonly arise from surgeons who deal with this disease. These include whether the patient has post-traumatic stiff elbow, how to evaluate the problem, when surgery is appropriate, how to perform an excellent arthrolysis, what the optimal postoperative rehabilitation is, and how to prevent or reduce the incidence of complications. Following these questions, this review provides an update and overview of post-traumatic elbow stiffness with respect to the diagnosis, preoperative evaluation, arthrolysis strategies, postoperative rehabilitation, and prevention of complications, aiming to provide a complete diagnosis and treatment path.

Cite this article: Bone Joint Open 2020;1-9:576–584.