There is no absolute method of evaluating healing
of a fracture of the tibial shaft. In this study we sought to validate a
new clinical method based on the systematic observation of gait,
first by assessing the degree of agreement between three independent
observers regarding the gait score for a given patient, and secondly
by determining how such a score might predict healing of a fracture. We used a method of evaluating gait to assess 33 patients (29
men and four women, with a mean age of 29 years (15 to 62)) who
had sustained an isolated fracture of the tibial shaft and had been
treated with a locked intramedullary nail. There were 15 closed
and 18 open fractures (three Gustilo and Anderson grade I, seven
grade II, seven grade IIIA and one grade IIIB). Assessment was carried
out three and six months post-operatively using videos taken with
a digital camera. Gait was graded on a scale ranging from 1 (extreme
difficulty) to 4 (normal gait). Bivariate analysis included analysis
of variance to determine whether the gait score statistically correlated
with previously validated and standardised scores of clinical status
and radiological evidence of union. An association was found between the pattern of gait and all
the other variables. Improvement in gait was associated with the
absence of pain on weight-bearing, reduced tenderness over the fracture,
a higher Radiographic Union Scale in Tibial Fractures score, and
improved functional status, measured using the Brazilian version
of the Short Musculoskeletal Function Assessment questionnaire (all
p <
0.001). Although further study is needed, the analysis of
gait in this way may prove to be a useful clinical tool.
This study validates the short-form WOMAC function scale for assessment of conservative treatment of osteoarthritis of the knee. Data were collected before treatment and six and nine months later, from 100 patients with osteoarthritis of the knee to determine the validity, internal consistency, test-retest reliability, floor and ceiling effects, and responsiveness of the short-form WOMAC function scale. The scale showed high correlation with the traditional WOMAC and other measures. The internal consistency was good (Cronbach α: 0.88 to 0.95) and an excellent test-retest reliability was found (Lin’s concordance correlation coefficient (ρc): 0.85 to 0.94). The responsiveness was adequate and comparable to that of the traditional WOMAC (standardised response mean 0.56 to 0.44 and effect size 0.64 to 0.57) and appeared not to be significantly affected by floor or ceiling effects (0% and 7%, respectively). The short-form WOMAC function scale is a valid, reliable and responsive alternative to the traditional WOMAC in the evaluation of patients with osteoarthritis of the knee managed conservatively. It is simple to use in daily practice and is therefore less of a burden for patients in clinical trials.
There have been considerable recent advances in the understanding and management of femoroacetabular impingement and associated labral and chondral pathology. We have developed a classification system for acetabular chondral lesions. In our system, we use the six acetabular zones previously described by Ilizaliturri et al. The cartilage is then graded on a scale of 0 to 4 as follows: grade 0, normal articular cartilage lesions; grade 1, softening or wave sign; grade 2, cleavage lesion; grade 3, delamination; and grade 4, exposed bone. The site of the lesion is further classed as A, B or C based on whether the lesion is less than one-third of the distance from the acetabular rim to the cotyloid fossa, one-third to two-thirds of the same distance and greater than two-thirds of the distance, respectively. In order to validate the classification system, six surgeons graded ten video recordings of hip arthroscopy. Our findings showed a high intra-observer reliability of the classification system with an intraclass correlation coefficient of 0.81 and a high interobserver reliability with an intraclass correlation coefficient of 0.88. We have developed a simple reproducible classification system for lesions of the acetabular cartilage, which it is hoped will allow standardised documentation to be made of damage to the articular cartilage, particularly that associated with femoroacetabular impingement.
The Oxford hip score (OHS) is a 12-item questionnaire designed
and developed to assess function and pain from the perspective of
patients who are undergoing total hip replacement (THR). The OHS
has been shown to be consistent, reliable, valid and sensitive to
clinical change following THR. It has been translated into different
languages, but no adequately translated, adapted and validated Danish
language version exists. The OHS was translated and cross-culturally adapted into Danish
from the original English version, using methods based on best-practice
guidelines. The translation was tested for psychometric quality
in patients drawn from a cohort from the Danish Hip Arthroplasty
Register (DHR).Objectives
Methods
This study demonstrates a significant correlation
between the American Knee Society (AKS) Clinical Rating System and
the Oxford Knee Score (OKS) and provides a validated prediction
tool to estimate score conversion. A total of 1022 patients were prospectively clinically assessed
five years after TKR and completed AKS assessments and an OKS questionnaire.
Multivariate regression analysis demonstrated significant correlations between
OKS and the AKS knee and function scores but a stronger correlation
(r = 0.68, p <
0.001) when using the sum of the AKS knee and
function scores. Addition of body mass index and age (other statistically
significant predictors of OKS) to the algorithm did not significantly
increase the predictive value. The simple regression model was used to predict the OKS in a
group of 236 patients who were clinically assessed nine to ten years
after TKR using the AKS system. The predicted OKS was compared with
actual OKS in the second group. Intra-class correlation demonstrated
excellent reliability (r = 0.81, 95% confidence intervals 0.75 to
0.85) for the combined knee and function score when used to predict
OKS. Our findings will facilitate comparison of outcome data from
studies and registries using either the OKS or the AKS scores and
may also be of value for those undertaking meta-analyses and systematic
reviews. Cite this article:
We undertook a study on eight arms from fresh cadavers to define the clinical usefulness of the lesser sigmoid notch as a landmark when reconstructing the length of the neck of the radius in replacement of the head with a prosthesis. The head was resected and its height measured, along with several control measurements. This was compared with The results were highly reproducible with intra- and interclass correlations of >
0.99. The mean difference between the measurement on the excised head and the distance from the stump of the neck and the lesser sigmoid notch was −0.02 mm (−1.24 to +0.97). This difference was not statistically significant (p = 0.78). The proximal edge of the lesser sigmoid notch provides a reliable landmark for positioning a replacement of the radial head and may have clinical application.
Aims. The aim of this study was to assess whether supine flexibility predicts the likelihood of curve progression in patients with adolescent idiopathic scoliosis (AIS) undergoing brace treatment. Methods. This was a retrospective analysis of patients with AIS prescribed with an underarm brace between September 2008 to April 2013 and followed up until 18 years of age or required surgery. Patients with structural proximal curves that preclude underarm bracing, those who were lost to follow-up, and those who had poor compliance to bracing (<16 hours a day) were excluded. The major curve Cobb angle, curve type, and location were measured on the pre-brace standing posteroanterior (PA) radiograph, supine whole spine radiograph, initial in-brace standing PA radiograph, and the post-brace weaning standing PA radiograph.
Aims. The aim of the British Association for Surgery of the Knee (BASK) Meniscal Consensus Project was to develop an evidence-based treatment guideline for patients with meniscal lesions of the knee. Materials and Methods. A formal consensus process was undertaken applying nominal group, Delphi, and appropriateness methods. Consensus was first reached on the terminology relating to the definition, investigation, and classification of meniscal lesions. A series of simulated clinical scenarios was then created and the appropriateness of arthroscopic meniscal surgery or nonoperative treatment in each scenario was rated by the group. The process was informed throughout by the latest published, and previously unpublished, clinical and epidemiological evidence. Scenarios were then grouped together based upon the similarity of clinical features and ratings to form the guideline for treatment. Feedback on the draft guideline was sought from the entire membership of BASK before final revisions and approval by the consensus group. Results. A total of 45 simulated clinical scenarios were refined to five common clinical presentations and six corresponding treatment recommendations. The final guideline stratifies patients based upon a new, standardized classification of symptoms, signs, radiological findings, duration of symptoms, and previous treatment. Conclusion. The 2018 BASK Arthroscopic Meniscal Surgery Treatment Guidance will facilitate the consistent identification and treatment of patients with meniscal lesions. It is hoped that this guidance will be adopted nationally by surgeons and help inform healthcare commissioning guidance.
Aims. This paper describes the methodology, validation and reliability
of a new computer-assisted method which uses models of the patient’s
bones and the components to measure their migration and polyethylene
wear from radiographs after total hip arthroplasty (THA). Materials and Methods. Models of the patient’s acetabular and femoral component obtained
from the manufacturer and models of the patient’s pelvis and femur
built from a single computed tomography (CT) scan, are used by a
computer program to measure the migration of the components and
the penetration of the femoral head from anteroposterior and lateral radiographs
taken at follow-up visits. The program simulates the radiographic
setup and matches the position and orientation of the models to
outlines of the pelvis, the acetabular and femoral component, and
femur on radiographs. Changes in position and orientation reflect
the migration of the components and the penetration of the femoral
head.
Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
Surgical site infection (SSI) after soft-tissue sarcoma (STS) resection is a serious complication. The purpose of this retrospective study was to investigate the risk factors for SSI after STS resection, and to develop a nomogram that allows patient-specific risk assessment. A total of 547 patients with STS who underwent tumour resection between 2005 and 2021 were divided into a development cohort and a validation cohort. In the development cohort of 402 patients, the least absolute shrinkage and selection operator (LASSO) regression model was used to screen possible risk factors of SSI. To select risk factors and construct the prediction nomogram, multivariate logistic regression was used. The predictive power of the nomogram was evaluated by receiver operating curve (ROC) analysis in the validation cohort of 145 patients.Aims
Methods
Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this annotation, we aim to provide an overview of the available prediction tools for eSTS, provide an approach for clinicians to evaluate the performance and usefulness of the available tools for their own patients, and discuss their possible applications in the management of patients with an eSTS. Cite this article:
This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue. The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed.Aims
Methods
To explore the novel molecular mechanisms of histone deacetylase 4 (HDAC4) in chondrocytes via RNA sequencing (RNA-seq) analysis. Empty adenovirus (EP) and a Aims
Methods
An objective technological solution for tracking adherence to at-home shoulder physiotherapy is important for improving patient engagement and rehabilitation outcomes, but remains a significant challenge. The aim of this research was to evaluate performance of machine-learning (ML) methodologies for detecting and classifying inertial data collected during in-clinic and at-home shoulder physiotherapy exercise. A smartwatch was used to collect inertial data from 42 patients performing shoulder physiotherapy exercises for rotator cuff injuries in both in-clinic and at-home settings. A two-stage ML approach was used to detect out-of-distribution (OOD) data (to remove non-exercise data) and subsequently for classification of exercises. We evaluated the performance impact of grouping exercises by motion type, inclusion of non-exercise data for algorithm training, and a patient-specific approach to exercise classification. Algorithm performance was evaluated using both in-clinic and at-home data.Aims
Methods
Radiological residual acetabular dysplasia (RAD) has been reported in up to 30% of children who had successful brace treatment of infant developmental dysplasia of the hip (DDH). Predicting those who will resolve and those who may need corrective surgery is important to optimize follow-up protocols. In this study we have aimed to identify the prevalence and predictors of RAD at two years and five years post-bracing. This was a single-centre, prospective longitudinal cohort study of infants with DDH managed using a published, standardized Pavlik harness protocol between January 2012 and December 2016. RAD was measured at two years’ mean follow-up using acetabular index-lateral edge (AI-L) and acetabular index-sourcil (AI-S), and at five years using AI-L, AI-S, centre-edge angle (CEA), and acetabular depth ratio (ADR). Each hip was classified based on published normative values for normal, borderline (1 to 2 standard deviations (SDs)), or dysplastic (> 2 SDs) based on sex, age, and laterality.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
Isolated fractures of the ulnar diaphysis are uncommon, occurring at a rate of 0.02 to 0.04 per 1,000 cases. Despite their infrequency, these fractures commonly give rise to complications, such as nonunion, limited forearm pronation and supination, restricted elbow range of motion, radioulnar synostosis, and prolonged pain. Treatment options for this injury remain a topic of debate, with limited research available and no consensus on the optimal approach. Therefore, this trial aims to compare clinical, radiological, and functional outcomes of two treatment methods: open reduction and internal fixation (ORIF) versus nonoperative treatment in patients with isolated ulnar diaphyseal fractures. This will be a multicentre, open-label, parallel randomized clinical trial (under National Clinical Trial number NCT01123447), accompanied by a parallel prospective cohort group for patients who meet the inclusion criteria, but decline randomization. Eligible patients will be randomized to one of the two treatment groups: 1) nonoperative treatment with closed reduction and below-elbow casting; or 2) surgical treatment with ORIF utilizing a limited contact dynamic compression plate and screw construct. The primary outcome measured will be the Disabilities of the Arm, Shoulder and Hand questionnaire score at 12 months post-injury. Additionally, functional outcomes will be assessed using the 36-Item Short Form Health Survey and pain visual analogue scale, allowing for a comparison of outcomes between groups. Secondary outcome measures will encompass clinical outcomes such as range of motion and grip strength, radiological parameters including time to union, as well as economic outcomes assessed from enrolment to 12 months post-injury.Aims
Methods
To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models.Aims
Methods