Aims. To investigate if preoperative CT improves detection of unstable trochanteric hip fractures. Methods. A single-centre prospective study was conducted. Patients aged 65 years or older with trochanteric hip fractures admitted to Stavanger University Hospital (Stavanger, Norway) were consecutively included from September 2020 to January 2022. Radiographs and CT images of the fractures were obtained, and surgeons made individual assessments of the fractures based on these. The assessment was conducted according to a systematic protocol including three classification systems (AO/Orthopaedic Trauma Association (OTA), Evans Jensen (EVJ), and Nakano) and questions addressing specific fracture patterns. An expert group provided a gold-standard assessment based on the CT images. Sensitivities and specificities of surgeons’ assessments were estimated and compared in regression models with correlations for the same patients. Intra- and inter-rater
Interobserver
Our aim was to assess the reproducibility and the
We evaluated the impact of stereo-visualisation of three-dimensional volume-rendering CT datasets on the inter- and intraobserver
Aims. To evaluate interobserver
The most widely used classification system for
acetabular fractures was developed by Judet, Judet and Letournel over
50 years ago primarily to aid surgical planning. As population demographics
and injury mechanisms have altered over time, the fracture patterns
also appear to be changing. We conducted a retrospective review
of the imaging of 100 patients with a mean age of 54.9 years (19
to 94) and a male to female ratio of 69:31 seen between 2010 and
2013 with acetabular fractures in order to determine whether the
current spectrum of injury patterns can be reliably classified using
the original system. Three consultant pelvic and acetabular surgeons and one senior
fellow analysed anonymous imaging. Inter-observer agreement for
the classification of fractures that fitted into defined categories
was substantial, (κ = 0.65, 95% confidence interval (CI) 0.51 to
0.76) with improvement to near perfect on inclusion of CT imaging
(κ = 0.80, 95% CI 0.69 to 0.91). However, a high proportion of injuries
(46%) were felt to be unclassifiable by more than one surgeon; there
was moderate agreement on which these were (κ = 0.42 95% CI 0.31
to 0.54). Further review of the unclassifiable fractures in this cohort
of 100 patients showed that they tended to occur in an older population
(mean age 59.1 years; 22 to 94 Cite this article:
Aims. Though most humeral shaft fractures heal nonoperatively, up to one-third may lead to nonunion with inferior outcomes. The Radiographic Union Score for HUmeral Fractures (RUSHU) was created to identify high-risk patients for nonunion. Our study evaluated the RUSHU’s prognostic performance at six and 12 weeks in discriminating nonunion within a significantly larger cohort than before. Methods. Our study included 226 nonoperatively treated humeral shaft fractures. We evaluated the interobserver
Aims. The aim of this study was to develop a psychometrically sound measure of recovery for use in patients who have suffered an open tibial fracture. Methods. An initial pool of 109 items was generated from previous qualitative data relating to recovery following an open tibial fracture. These items were field tested in a cohort of patients recovering from an open tibial fracture. They were asked to comment on the content of the items and structure of the scale. Reduction in the number of items led to a refined scale tested in a larger cohort of patients. Principal components analysis permitted further reduction and the development of a definitive scale. Internal consistency, test-retest
Objectives. Patient-reported outcome measures (PROMs) are often used to evaluate the outcome of treatment in patients with distal radial fractures. Which PROM to select is often based on assessment of measurement properties, such as validity and
Objectives. The radiographic union score for tibial (RUST) fractures was developed by Whelan et al to assess the healing of tibial fractures following intramedullary nailing. In the current study, the repeatability and
The purpose of this study was to develop a convolutional neural network (CNN) for fracture detection, classification, and identification of greater tuberosity displacement ≥ 1 cm, neck-shaft angle (NSA) ≤ 100°, shaft translation, and articular fracture involvement, on plain radiographs. The CNN was trained and tested on radiographs sourced from 11 hospitals in Australia and externally validated on radiographs from the Netherlands. Each radiograph was paired with corresponding CT scans to serve as the reference standard based on dual independent evaluation by trained researchers and attending orthopaedic surgeons. Presence of a fracture, classification (non- to minimally displaced; two-part, multipart, and glenohumeral dislocation), and four characteristics were determined on 2D and 3D CT scans and subsequently allocated to each series of radiographs. Fracture characteristics included greater tuberosity displacement ≥ 1 cm, NSA ≤ 100°, shaft translation (0% to < 75%, 75% to 95%, > 95%), and the extent of articular involvement (0% to < 15%, 15% to 35%, or > 35%).Aims
Methods
We describe the routine imaging practices of
Level 1 trauma centres for patients with severe pelvic ring fractures, and
the interobserver
The aims of this study were to assess quality of life after hip fractures, to characterize respondents to patient-reported outcome measures (PROMs), and to describe the recovery trajectory of hip fracture patients. Data on 35,206 hip fractures (2014 to 2018; 67.2% female) in the Norwegian Hip Fracture Register were linked to data from the Norwegian Patient Registry and Statistics Norway. PROMs data were collected using the EuroQol five-dimension three-level questionnaire (EQ-5D-3L) scoring instrument and living patients were invited to respond at four, 12, and 36 months post fracture. Multiple imputation procedures were performed as a model to substitute missing PROM data. Differences in response rates between categories of covariates were analyzed using chi-squared test statistics. The association between patient and socioeconomic characteristics and the reported EQ-5D-3L scores was analyzed using linear regression.Aims
Methods
Current levels of hip fracture morbidity contribute greatly to the overall burden on health and social care services. Given the anticipated ageing of the population over the coming decade, there is potential for this burden to increase further, although the exact scale of impact has not been identified in contemporary literature. We therefore set out to predict the future incidence of hip fracture and help inform appropriate service provision to maintain an adequate standard of care. Historical data from the Scottish Hip Fracture Audit (2017 to 2021) were used to identify monthly incidence rates. Established time series forecasting techniques (Exponential Smoothing and Autoregressive Integrated Moving Average) were then used to predict the annual number of hip fractures from 2022 to 2029, including adjustment for predicted changes in national population demographics. Predicted differences in service-level outcomes (length of stay and discharge destination) were analyzed, including the associated financial cost of any changes.Aims
Methods
Frailty greatly increases the risk of adverse outcome of trauma in older people. Frailty detection tools appear to be unsuitable for use in traumatically injured older patients. We therefore aimed to develop a method for detecting frailty in older people sustaining trauma using routinely collected clinical data. We analyzed prospectively collected registry data from 2,108 patients aged ≥ 65 years who were admitted to a single major trauma centre over five years (1 October 2015 to 31 July 2020). We divided the sample equally into two, creating derivation and validation samples. In the derivation sample, we performed univariate analyses followed by multivariate regression, starting with 27 clinical variables in the registry to predict Clinical Frailty Scale (CFS; range 1 to 9) scores. Bland-Altman analyses were performed in the validation cohort to evaluate any biases between the Nottingham Trauma Frailty Index (NTFI) and the CFS.Aims
Methods
Ankle fracture fixation is commonly performed by junior trainees. Simulation training using cadavers may shorten the learning curve and result in a technically superior surgical performance. We undertook a preliminary, pragmatic, single-blinded, multicentre, randomized controlled trial of cadaveric simulation versus standard training. Primary outcome was fracture reduction on postoperative radiographs.Aims
Methods
To evaluate if, for orthopaedic trainees, additional cadaveric simulation training or standard training alone yields superior radiological and clinical outcomes in patients undergoing dynamic hip screw (DHS) fixation or hemiarthroplasty for hip fracture. This was a preliminary, pragmatic, multicentre, parallel group randomized controlled trial in nine secondary and tertiary NHS hospitals in England. Researchers were blinded to group allocation. Overall, 40 trainees in the West Midlands were eligible: 33 agreed to take part and were randomized, five withdrew after randomization, 13 were allocated cadaveric training, and 15 were allocated standard training. The intervention was an additional two-day cadaveric simulation course. The control group received standard on-the-job training. Primary outcome was implant position on the postoperative radiograph: tip-apex distance (mm) (DHS) and leg length discrepancy (mm) (hemiarthroplasty). Secondary clinical outcomes were procedure time, length of hospital stay, acute postoperative complication rate, and 12-month mortality. Procedure-specific secondary outcomes were intraoperative radiation dose (for DHS) and postoperative blood transfusion requirement (hemiarthroplasty).Aims
Methods
Prior to the availability of vaccines, mortality for hip fracture patients with concomitant COVID-19 infection was three times higher than pre-pandemic rates. The primary aim of this study was to determine the 30-day mortality rate of hip fracture patients in the post-vaccine era. A multicentre observational study was carried out at 19 NHS Trusts in England. The study period for the data collection was 1 February 2021 until 28 February 2022, with mortality tracing until 28 March 2022. Data collection included demographic details, data points to calculate the Nottingham Hip Fracture Score, COVID-19 status, 30-day mortality, and vaccination status.Aims
Methods
We introduced a self-care pathway for minimally displaced distal radius fractures, which involved the patient being discharged from a Virtual Fracture Clinic (VFC) without a physical review and being provided with written instructions on how to remove their own cast or splint at home, plus advice on exercises and return to function. All patients managed via this protocol between March and October 2020 were contacted by a medical secretary at a minimum of six months post-injury. The patients were asked to complete the Patient-Rated Wrist Evaluation (PRWE), a satisfaction questionnaire, advise if they had required surgery and/or contacted any health professional, and were also asked for any recommendations on how to improve the service. A review with a hand surgeon was organized if required, and a cost analysis was also conducted.Aims
Methods
The aim of this study was to describe the demographic details of patients who sustain a femoral periprosthetic fracture (PPF), the epidemiology of PPFs, PPF characteristics, and the predictors of PPF types in the UK population. This is a multicentre retrospective cohort study including adult patients presenting to hospital with a new PPF between 1 January 2018 and 31 December 2018. Data collected included: patient characteristics, comorbidities, anticoagulant use, social circumstances, level of mobility, fracture characteristics, Unified Classification System (UCS) type, and details of the original implant. Descriptive analysis by fracture location was performed, and predictors of PPF type were assessed using mixed-effects logistic regression models.Aims
Methods