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,
To assess if older symptomatic children with club foot deformity differ in perceived disability and foot function during gait, depending on initial treatment with Ponseti or surgery, compared to a control group. Second aim was to investigate correlations between foot function during gait and perceived disability in this population. In all, 73 children with idiopathic club foot were included: 31 children treated with the Ponseti method (mean age 8.3 years; 24 male; 20 bilaterally affected, 13 left and 18 right sides analyzed), and 42 treated with primary surgical correction (mean age 11.6 years; 28 male; 23 bilaterally affected, 18 left and 24 right sides analyzed). Foot function data was collected during walking gait and included Oxford Foot Model kinematics (Foot Profile Score and the range of movement and average position of each part of the foot) and plantar pressure (peak pressure in five areas of the foot). Oxford Ankle Foot Questionnaire, Disease Specific Index for club foot, Paediatric Quality of Life Inventory 4.0 were also collected. The gait data were compared between the two club foot groups and compared to control data. The gait data were also correlated with the data extracted from the questionnaires.Aims
Methods
This study aims to define the epidemiology of trauma presenting to a single centre providing all orthopaedic trauma care for a population of ∼ 900,000 over the first 40 days of the COVID-19 pandemic compared to that presenting over the same period one year earlier. The secondary aim was to compare this with population mobility data obtained from Google. A cross-sectional study of consecutive adult (> 13 years) patients with musculoskeletal trauma referred as either in-patients or out-patients over a 40-day period beginning on 5 March 2020, the date of the first reported UK COVID-19 death, was performed. This time period encompassed social distancing measures. This group was compared to a group of patients referred over the same calendar period in 2019 and to publicly available mobility data from Google.Aims
Methods
