The standard of wide tumour-like resection for chronic osteomyelitis (COM) has been challenged recently by adequate debridement. This paper reviews the evolution of surgical debridement for long bone COM, and presents the outcome of adequate debridement in a tertiary bone infection unit. We analyzed the retrospective record review from 2014 to 2020 of patients with long bone COM. All were managed by multidisciplinary infection team (MDT) protocol. Adequate debridement was employed for all cases, and no case of wide resection was included.Aims
Methods
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. 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).Aims
Methods
