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
Plots are an elegant and effective way to represent
data. At their best they encourage the reader and promote comprehension.
A graphical representation can give a far more intuitive feel to
the pattern of results in the study than a list of numerical data,
or the result of a statistical calculation. The temptation to exaggerate differences or relationships between
variables by using broken axes, overlaid axes, or inconsistent scaling
between plots should be avoided. A plot should be self-explanatory and not complicated. It should
make good use of the available space. The axes should be scaled
appropriately and labelled with an appropriate dimension. Plots are recognised statistical methods of presenting data and
usually require specialised statistical software to create them.
The statistical analysis and methods to generate the plots are as
important as the methodology of the study itself. The software,
including dates and version numbers, as well as statistical tests
should be appropriately referenced. Following some of the guidance provided in this article will
enhance a manuscript. Cite this article:
We examined the rates of infection and colonisation by methicillin-resistant In 2004, we screened 1795 of 1796 elective admissions and MRSA was found in 23 (1.3%). We also screened 1122 of 1447 trauma admissions and 43 (3.8%) were carrying MRSA. All ten ward transfers were screened and four (40%) were carriers (all p <
0.001). The incidence of MRSA in trauma patients increased by 2.6% per week of inpatient stay (r = 0.97, p <
0.001). MRSA developed in 2.9% of trauma and 0.2% of elective patients during that admission (p <
0.001). The implementation of the MRSA policy reduced the incidence of MRSA infection by 56% in trauma patients (1.57% in 2003 (17 of 1084) to 0.69% in 2004 (10 of 1447), p = 0.035). Infection with MRSA in elective patients was reduced by 70% (0.56% in 2003 (7 of 1257) to 0.17% in 2004 (3 of 1806), p = 0.06). The cost of preventing one MRSA infection was £3200. Although colonisation by MRSA did not affect the mortality rate, infection by MRSA more than doubled it. Patients with proximal fractures of the femur infected with MRSA remained in hospital for 50 extra days, had 19 more days of vancomycin treatment and 26 more days of vacuum-assisted closure therapy than the matched controls. These additional costs equated to £13 972 per patient. From this experience we have been able to describe the epidemiology of MRSA, assess the impact of infection-control measures on MRSA infection rates and determine the morbidity, mortality and economic cost of MRSA carriage on trauma and elective orthopaedic wards.