To investigate psychosocial and biomedical outcomes following
total hip replacement (THR) and to identify predictors of recovery
from THR. Patients with osteoarthritis (OA) on the waiting list for primary
THR in North West England were assessed pre-operatively and at six
and 12 months post-operatively to investigate psychosocial and biomedical
outcomes. Psychosocial outcomes were anxiety and depression, social
support and health-related quality of life (HRQoL). Biomedical outcomes
were pain, physical function and stiffness. The primary outcome
was the Short-Form 36 (SF-36) Health Survey Total Physical Function.
Potential predictors of outcome were age, sex, body mass index,
previous joint replacement, involvement in the decision for THR,
any comorbidities, any complications, type of medication, and pre-operative
ENRICHD Social Support Instrument score, Hospital Anxiety and Depression
scores and Western Ontario and McMaster Universities osteoarthritis index
score.Objectives
Methods
Sickle cell disease (SCD) is an autosomal recessive inherited condition that presents with a number of clinical manifestations that include musculoskeletal manifestations (MM). MM may present differently in different individuals and settings and the predictors are not well known. Herein, we aimed at determining the predictors of MM in patients with SCD at the University Teaching Hospital, Lusaka, Zambia. An unmatched case-control study was conducted between January and May 2019 in children below the age of 16 years. In all, 57 cases and 114 controls were obtained by systematic sampling method. A structured questionnaire was used to collect data. The different MM were identified, staged, and classified according to the Standard Orthopaedic Classification Systems using radiological and laboratory investigations. The data was entered in Epidata version 3.1 and exported to STATA 15 for analysis. Multiple logistic regression was used to determine predictors and predictive margins were used to determine the probability of MM.Aims
Methods
Repeated lumbar spine surgery has been associated with inferior clinical outcomes. This study aimed to examine and quantify the impact of this association in a national clinical register cohort. This is a population-based study from the Norwegian Registry for Spine surgery (NORspine). We included 26,723 consecutive cases operated for lumbar spinal stenosis or lumbar disc herniation from January 2007 to December 2018. The primary outcome was the Oswestry Disability Index (ODI), presented as the proportions reaching a patient-acceptable symptom state (PASS; defined as an ODI raw score ≤ 22) and ODI raw and change scores at 12-month follow-up. Secondary outcomes were the Global Perceived Effect scale, the numerical rating scale for pain, the EuroQoL five-dimensions health questionnaire, occurrence of perioperative complications and wound infections, and working capability. Binary logistic regression analysis was conducted to examine how the number of previous operations influenced the odds of not reaching a PASS.Aims
Methods
The aims of this study were to assess mapping models to predict the three-level version of EuroQoL five-dimension utility index (EQ-5D-3L) from the Oxford Knee Score (OKS) and validate these before and after total knee arthroplasty (TKA). A retrospective cohort of 5,857 patients was used to create the prediction models, and a second cohort of 721 patients from a different centre was used to validate the models, all of whom underwent TKA. Patient characteristics, BMI, OKS, and EQ-5D-3L were collected preoperatively and one year postoperatively. Generalized linear regression was used to formulate the prediction models.Aims
Methods
The aim of this study was to develop and internally validate a prognostic nomogram to predict the probability of gaining a functional range of motion (ROM ≥ 120°) after open arthrolysis of the elbow in patients with post-traumatic stiffness of the elbow. We developed the Shanghai Prediction Model for Elbow Stiffness Surgical Outcome (SPESSO) based on a dataset of 551 patients who underwent open arthrolysis of the elbow in four institutions. Demographic and clinical characteristics were collected from medical records. The least absolute shrinkage and selection operator regression model was used to optimize the selection of relevant features. Multivariable logistic regression analysis was used to build the SPESSO. Its prediction performance was evaluated using the concordance index (C-index) and a calibration graph. Internal validation was conducted using bootstrapping validation.Aims
Methods
Aims. The aim of this study was to investigate the association between fracture displacement and survivorship of the native hip joint without conversion to a total hip arthroplasty (THA), and to determine predictors for conversion to THA in patients treated nonoperatively for acetabular fractures. Methods. A multicentre cross-sectional study was performed in 170 patients who were treated nonoperatively for an acetabular fracture in three level 1 trauma centres. Using the post-injury diagnostic CT scan, the maximum gap and step-off values in the weightbearing dome were digitally measured by two trauma surgeons. Native hip survival was reported using Kaplan-Meier curves.
Objectives. Few studies have assessed outcomes following non-metal-on-metal hip arthroplasty (non-MoMHA) revision surgery performed for adverse reactions to metal debris (ARMD). We assessed outcomes following non-MoMHA revision surgery performed for ARMD, and identified predictors of re-revision. Methods. We performed a retrospective observational study using data from the National Joint Registry for England and Wales. All non-MoMHAs undergoing revision surgery for ARMD between 2008 and 2014 were included (185 hips in 185 patients). Outcome measures following ARMD revision were intra-operative complications, mortality and re-revision surgery.
Aims. To determine the outcomes following revision surgery of metal-on-metal
hip arthroplasties (MoMHA) performed for adverse reactions to metal
debris (ARMD), and to identify factors predictive of re-revision. Patients and Methods. We performed a retrospective observational study using National
Joint Registry (NJR) data on 2535 MoMHAs undergoing revision surgery
for ARMD between 2008 and 2014. The outcomes studied following revision were
intra-operative complications, mortality and re-revision surgery.
Predictors of re-revision were identified using competing-risk regression
modelling. Results. Intra-operative complications occurred in 40 revisions (1.6%).
The cumulative five-year patient survival rate was 95.9% (95% confidence
intervals (CI) 92.3 to 97.8). Re-revision surgery was performed
in 192 hips (7.6%). The cumulative five-year implant survival rate
was 89.5% (95% CI 87.3 to 91.3).
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:
Shoulder arthroplasty is effective in the management of end-stage glenohumeral joint arthritis. However, it is major surgery and patients must balance multiple factors when considering the procedure. An understanding of patients’ decision-making processes may facilitate greater support of those considering shoulder arthroplasty and inform the outcomes of future research. Participants were recruited from waiting lists of three consultant upper limb surgeons across two NHS hospitals. Semi-structured interviews were conducted with 12 participants who were awaiting elective shoulder arthroplasty. Transcribed interviews were analyzed using a grounded theory approach. Systematic coding was performed; initial codes were categorized and further developed into summary narratives through a process of discussion and refinement. Data collection and analyses continued until thematic saturation was reached.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
Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool. A systematic search screening 3,252 studies identified 45 ML-based prediction models in orthopaedic trauma up to January 2023. The TRIPOD statement assessed transparent reporting and the PROBAST tool the risk of bias.Aims
Methods
In-hospital length of stay (LOS) and discharge dispositions following arthroplasty could act as surrogate measures for improvement in patient pathways, and have major cost saving implications for healthcare providers. With the ever-growing adoption of robotic technology in arthroplasty, it is imperative to evaluate its impact on LOS. The objectives of this study were to compare LOS and discharge dispositions following robotic arm-assisted total knee arthroplasty (RO TKA) and unicompartmental arthroplasty (RO UKA) versus conventional technique (CO TKA and UKA). This large-scale, single-institution study included patients of any age undergoing primary TKA (n = 1,375) or UKA (n = 337) for any cause between May 2019 and January 2023. Data extracted included patient demographics, LOS, need for post anaesthesia care unit (PACU) admission, anaesthesia type, readmission within 30 days, and discharge dispositions. Univariate and multivariate logistic regression models were also employed to identify factors and patient characteristics related to delayed discharge.Aims
Methods
The aim of this study was to review the current evidence surrounding curve type and morphology on curve progression risk in adolescent idiopathic scoliosis (AIS). A comprehensive search was conducted by two independent reviewers on PubMed, Embase, Medline, and Web of Science to obtain all published information on morphological predictors of AIS progression. Search items included ‘adolescent idiopathic scoliosis’, ‘progression’, and ‘imaging’. The inclusion and exclusion criteria were carefully defined. Risk of bias of studies was assessed with the Quality in Prognostic Studies tool, and level of evidence for each predictor was rated with the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. In all, 6,286 publications were identified with 3,598 being subjected to secondary scrutiny. Ultimately, 26 publications (25 datasets) were included in this review.Aims
Methods
The primary aim was to estimate the cost-effectiveness of routine operative fixation for all patients with humeral shaft fractures. The secondary aim was to estimate the health economic implications of using a Radiographic Union Score for HUmeral fractures (RUSHU) of < 8 to facilitate selective fixation for patients at risk of nonunion. From 2008 to 2017, 215 patients (mean age 57 yrs (17 to 18), 61% female (n = 130/215)) with a nonoperatively managed humeral diaphyseal fracture were retrospectively identified. Union was achieved in 77% (n = 165/215) after initial nonoperative management, with 23% (n = 50/215) uniting after surgery for nonunion. The EuroQol five-dimension three-level health index (EQ-5D-3L) was obtained via postal survey. Multiple regression was used to determine the independent influence of patient, injury, and management factors upon the EQ-5D-3L. An incremental cost-effectiveness ratio (ICER) of < £20,000 per quality-adjusted life-year (QALY) gained was considered cost-effective.Aims
Methods
The aim of this study was to conduct a cross-sectional, observational cohort study of patients presenting for revision of a total hip, or total or unicompartmental knee arthroplasty, to understand current routes to revision surgery and explore differences in symptoms, healthcare use, reason for revision, and the revision surgery (surgical time, components, length of stay) between patients having regular follow-up and those without. Data were collected from participants and medical records for the 12 months prior to revision. Patients with previous revision, metal-on-metal articulations, or hip hemiarthroplasty were excluded. Participants were retrospectively classified as ‘Planned’ or ‘Unplanned’ revision. Multilevel regression and propensity score matching were used to compare the two groups.Aims
Methods
The aim of this study was to determine satisfaction rates after hip and knee arthroplasty in patients who did not respond to postoperative patient-reported outcome measures (PROMs), characteristics of non-responders, and contact preferences to maximize response rates. A prospective cohort study of patients planned to undergo hip arthroplasty (n = 713) and knee arthroplasty (n = 737) at a UK university teaching hospital who had completed preoperative PROMs questionnaires, including the EuroQol five-dimension health-related quality of life score, and Oxford Hip Score (OHS) and Oxford Knee Score (OKS). Follow-up questionnaires were sent by post at one year, including satisfaction scoring. Attempts were made to contact patients who did not initially respond. Univariate, logistic regression, and receiver operator curve analysis was performed.Aims
Methods
The aim of this study was to assess the ability of morphological spinal parameters to predict the outcome of bracing in patients with adolescent idiopathic scoliosis (AIS) and to establish a novel supine correction index (SCI) for guiding bracing treatment. Patients with AIS to be treated by bracing were prospectively recruited between December 2016 and 2018, and were followed until brace removal. In all, 207 patients with a mean age at recruitment of 12.8 years (SD 1.2) were enrolled. Cobb angles, supine flexibility, and the rate of in-brace correction were measured and used to predict curve progression at the end of follow-up. The SCI was defined as the ratio between correction rate and flexibility. Receiver operating characteristic (ROC) curve analysis was carried out to assess the optimal thresholds for flexibility, correction rate, and SCI in predicting a higher risk of progression, defined by a change in Cobb angle of ≥ 5° or the need for surgery.Aims
Methods
Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.
The aim of this study was to investigate whether on-demand removal (ODR) is noninferior to routine removal (RR) of syndesmotic screws regarding functional outcome. Adult patients (aged above 17 years) with traumatic syndesmotic injury, surgically treated within 14 days of trauma using one or two syndesmotic screws, were eligible (n = 490) for inclusion in this randomized controlled noninferiority trial. A total of 197 patients were randomized for either ODR (retaining the syndesmotic screw unless there were complaints warranting removal) or RR (screw removed at eight to 12 weeks after syndesmotic fixation), of whom 152 completed the study. The primary outcome was functional outcome at 12 months after screw placement, measured by the Olerud-Molander Ankle Score (OMAS).Aims
Methods
