Hip resurfacing remains a potentially valuable surgical procedure for appropriately-selected patients with optimised implant choices. However, concern regarding high early failure rates continues to undermine confidence in use. A large contributor to failure is adverse local tissue reactions around metal-on-metal (MoM) bearing surfaces. Such phenomena have been well-explored around MoM total hip arthroplasties, but comparable data in equivalent hip resurfacing procedures is lacking. In order to define genetic predisposition, we performed a case-control study investigating the role of human leucocyte antigen (HLA) genotype in the development of pseudotumours around MoM hip resurfacings. A matched case-control study was performed using the prospectively-collected database at the host institution. In all, 16 MoM hip resurfacing 'cases' were identified as having symptomatic periprosthetic pseudotumours on preoperative metal artefact reduction sequence (MARS) MRI, and were subsequently histologically confirmed as high-grade aseptic lymphocyte-dominated vasculitis-associated lesions (ALVALs) at revision surgery. ‘Controls’ were matched by implant type in the absence of evidence of pseudotumour. Blood samples from all cases and controls were collected prospectively for high resolution genetic a nalysis targeting 11 separate HLA loci. Statistical significance was set at 0.10 a priori to determine the association between HLA genotype and pseudotumour formation, given the small sample size.Aims
Methods
Aims. Osteoporosis can determine surgical strategy for total hip arthroplasty (THA), and perioperative fracture risk. The aims of this study were to use hip CT to measure femoral bone mineral density (BMD) using CT X-ray absorptiometry (CTXA), determine if systematic evaluation of preoperative femoral BMD with CTXA would improve
This meta analysis address the relationship between infection developing after total hip arthroplasty (THA) and heterotopic ossification (HO). To identify the gaps in available knowledge, we screened for full-length peer-reviewed research articles listed in PubMed, Embase, and Web of Science over the past 20 years. The following search terms and Boolean operators were used: heterotopic ossification AND infection AND (hip replacement OR hip arthroplasty). The search resulted in the
Femoroacetabular Impingement (FAI) syndrome, characterised by abnormal hip contact causing symptoms and osteoarthritis, is measured using the International Hip Outcome Tool (iHOT). This study uses machine learning to predict patient outcomes post-treatment for FAI, focusing on achieving a minimally clinically important difference (MCID) at 52 weeks. A retrospective analysis of 6133 patients from the NAHR who underwent hip arthroscopic treatment for FAI between November 2013 and March 2022 was conducted. MCID was defined as half a standard deviation (13.61) from the mean change in iHOT score at 12 months. SKLearn Maximum Absolute Scaler and Logistic Regression were applied to predict achieving MCID, using baseline and 6-month follow-up data. The model's performance was evaluated by accuracy, area under the curve, and recall, using pre-operative and up to 6-month postoperative variables. A total of 23.1% (1422) of patients completed both baseline and 1-year follow-up iHOT surveys. The best results were obtained using both pre and postoperative variables. The machine learning model achieved 88.1% balanced accuracy, 89.6% recall, and 92.3% AUC. Sensitivity was 83.7% and specificity 93.5%. Key variables determining outcomes included MCID achievement at 6 months, baseline iHOT score, 6-month iHOT scores for pain, and difficulty in walking or using stairs. The study confirmed the utility of machine learning in predicting long-term outcomes following arthroscopic treatment for FAI. MCID, based on the iHOT 12 tools, indicates meaningful clinical changes. Machine learning demonstrated high accuracy and recall in distinguishing between patients achieving MCID and those who did not. This approach could help early
Hip prosthetic joint infection (PJI) is a debilitating complication following joint replacement surgery, with significant impact on patients and healthcare systems. The INFection ORthopaedic Management: Evidence into Practice (INFORM:EP) study, builds upon the 6-year INFORM programme by developing evidence-based guidelines for the
Dislocation after Total Hip Arthroplasty (THA) is a frequent cause of revision and patients with intrinsic risk factors have been identified. The use of dual mobility (DM) cup has shown great efficiency in preventing dislocation, with questions regarding selective or absolute use. The aim of this study was to compare the outcome of single mobility THA (SM-THA) and DM-THA, when used for selected patients. This retrospective continuous cohort study evaluated 490 patients of whom 275 received SM-THA and 215 received DM-THA. There were 304 primary osteoarthritis (62%), 121 femoral neck fractures (24%) and 65 other indications (14%). The surgical approach was anterior (AA) in 79% and posterior (PA) in 21% of cases. In the DM-THA group, 189 patients (87%) presented at least one dislocation risk factor compared to 128 patients (46%) in the SM-THA group. The primary outcome was revision for all causes, with or without implant removal. Secondary outcomes included length of hospital stay. There was no difference in all cause revision at two years follow up with 9 procedures (3.2%) in SM-THA group and 11 in DM-THA group (5.1%) (p=0.3). There were 3 dislocations in SM-THA group (3 AA) and 3 in DM-THA group (2 PA and 1 AA) (p=0.4). The length of stay was significantly longer in DM-THA group with 7 days (2–12) compared to 4 days (1–7) in SM-THA group (p=0.001). SM-THA and DM-THA are two complementary devices in the management of patients requiring primary THA. SM-THA is a safe option for patients without dislocation risk factors, especially when using AA. The
Musculoskeletal disorders have been recognised as common occupational risks for all orthopaedic surgeons. The nature of tasks performed by hip surgeons often requires both forceful and repetitive manoeuvres, potentially putting them at higher risk of musculoskeletal injuries compared to other orthopaedic sub-specialities. This study aimed to investigate the prevalence of musculoskeletal conditions among hip surgeons and evaluate the association between their workplace and lifestyle factors and musculoskeletal health. An online questionnaire consisting of 22 questions was distributed to UK-based consultant hip surgeons via email and social media platforms. This survey was completed by 105 hip surgeons. The mean age of the respondents was 49 years (range 35–69), with an average of 12 years (range 1–33) in service. 94% were full-time and 6% worked part-time. 49% worked at a district general hospital, 49% at a tertiary centre and 4% at a private institution. 80% were on the on-call rota and 69% had additional trauma commitments. 91% reported having one or more, 50% with three or more and 13% with five or more musculoskeletal conditions. 64% attributed their musculoskeletal condition to their profession. The most common musculoskeletal conditions were base of thumb arthritis (22%), subacromial impingement (20%), degenerative lumbar spine (18%) and medial or lateral epicondylitis (18%). 60% stated that they experienced lower back pain. Statistical analysis showed that being on the on-call rota was significantly (P<0.001) associated with a higher musculoskeletal burden. Regular resistance and/or endurance training and BMI<30 were statistically significant protective factors (P<0.001). Over the last few decades, most of the hip-related literature has focused on improving outcomes in patients, yet very little is known about the impact of hip surgery on the musculoskeletal health of hip surgeons. This study highlights a high prevalence of musculoskeletal conditions among UK-based hip surgeons. Hip surgeons have a pivotal role to play in the ongoing recovery of elective orthopaedics services. There is a pressing need for the
Aims. Transfusion after primary total hip arthroplasty (THA) has become rare, and
Electronic Health Records (EHRs) have benefits for hospitals and uptake in the UK is increasing. The National Joint Registry (NJR) monitors implant and surgeon performance and relies on accuracy of data. NJR data are used for
To examine whether Natural Language Processing (NLP) using a state-of-the-art clinically based Large Language Model (LLM) could predict patient selection for Total Hip Arthroplasty (THA), across a range of routinely available clinical text sources. Data pre-processing and analyses were conducted according to the Ai to Revolutionise the patient Care pathway in Hip and Knee arthroplasty (ARCHERY) project protocol (. https://www.researchprotocols.org/2022/5/e37092/. ). Three types of deidentified Scottish regional clinical free text data were assessed: Referral letters, radiology reports and clinic letters. NLP algorithms were based on the GatorTron model, a Bidirectional Encoder Representations from Transformers (BERT) based LLM trained on 82 billion words of de-identified clinical text. Three specific inference tasks were performed: assessment of the base GatorTron model, assessment after model-fine tuning, and external validation. There were 3911, 1621 and 1503 patient text documents included from the sources of referral letters, radiology reports and clinic letters respectively. All letter sources displayed significant class imbalance, with only 15.8%, 24.9%, and 5.9% of patients linked to the respective text source documentation having undergone surgery. Untrained model performance was poor, with F1 scores (harmonic mean of precision and recall) of 0.02, 0.38 and 0.09 respectively. This did however improve with model training, with mean scores (range) of 0.39 (0.31–0.47), 0.57 (0.48–0.63) and 0.32 (0.28–0.39) across the 5 folds of cross-validation. Performance deteriorated on external validation across all three groups but remained highest for the radiology report cohort. Even with further training on a large cohort of routinely collected free-text data a clinical LLM fails to adequately perform clinical inference in NLP tasks regarding
Two-stage exchange arthroplasty is traditionally used to treat periprosthetic hip infection. Nevertheless, particularly in high-risk patients, there has been increased attention towards alternatives such as 1.5-stage exchange arthroplasty which takes place in one surgery. Therefore, we sought to compare (1) operative time, length-of-stay (LOS), transfusions, (2) causative organism
Aims. This study aimed to evaluate sagittal spinopelvic alignment (SSPA) in the early stage of rapidly destructive coxopathy (RDC) compared with hip osteoarthritis (HOA), and to identify risk factors of SSPA for destruction of the femoral head within 12 months after the disease onset. Methods. This study enrolled 34 RDC patients with joint space narrowing > 2 mm within 12 months after the onset of hip pain and 25 HOA patients showing femoral head destruction. Sharp angle was measured for acetabular coverage evaluation. Femoral head collapse ratio was calculated for assessment of the extent of femoral head collapse by RDC. The following parameters of SSPA were evaluated using the whole spinopelvic radiograph: pelvic tilt (PT), sacral slope (SS), pelvic incidence (PI), sagittal vertical axis (SVA), thoracic kyphosis angle (TK), lumbar lordosis angle (LL), and PI-LL. Results. The HOA group showed higher Sharp angles compared with the RDC group. PT and PI-LL were higher in the RDC group than the HOA group. SS and LL were lower in the RDC group than the HOA group. No difference was found in PI, SVA, or TK between the groups. Femoral head collapse ratio was associated with PT, SS, SVA, LL, and PI-LL. A PI-LL > 20° and a PT > 30° correlated with greater extent of femoral head destruction by RDC. From regression analysis, SS and SVA were significantly associated with the femoral head collapse ratio within 12 months after disease onset. Conclusion. Compared with HOA, RDC in the early stage correlated with sagittal spinopelvic malalignment. SS and SVA may partially contribute to the extent of femoral head destruction by RDC within 12 months after the onset of hip pain. The present study indicates a potential role of SSPA assessment in
Aims. The primary aim was to determine the influence of COVID-19 on 30-day mortality following hip fracture. Secondary aims were to determine predictors of COVID-19 status on presentation and later in the admission; the rate of hospital acquired COVID-19; and the predictive value of negative swabs on admission. Methods. A nationwide multicentre retrospective cohort study was conducted of all patients presenting with a hip fracture to 17 Scottish centres in March and April 2020. Demographics, presentation blood tests, COVID-19 status, Nottingham Hip Fracture Score, management, length of stay, and 30-day mortality were recorded. Results. In all, 78/833 (9.4%) patients were diagnosed with COVID-19. The 30-day survival of patients with COVID-19 was significantly lower than for those without (65.4% vs 91%; p < 0.001). Diagnosis of COVID-19 within seven days of admission (likely community acquired) was independently associated with male sex (odds ratio (OR) 2.34, p = 0.040, confidence interval (CI) 1.04 to 5.25) and symptoms of COVID-19 (OR 15.56, CI 6.61 to 36.60, p < 0.001). Diagnosis of COVID-19 made between seven and 30 days of admission to hospital (likely hospital acquired) was independently associated with male sex (OR 1.73, CI 1.05 to 2.87, p = 0.032), Nottingham Hip Fracture Score ≥ 7 (OR 1.91, CI 1.09 to 3.34, p = 0.024), pulmonary disease (OR 1.68, CI 1.00 to 2.81, p = 0.049), American Society of Anesthesiologists (ASA) grade ≥ 3 (OR 2.37, CI 1.13 to 4.97, p = 0.022), and length of stay ≥ nine days (OR 1.98, CI 1.18 to 3.31, p = 0.009). A total of 38 (58.5%) COVID-19 cases were probably hospital acquired infections. The false-negative rate of a negative swab on admission was 0% in asymptomatic patients and 2.9% in symptomatic patients. Conclusion. COVID-19 was independently associated with a three times increased 30-day mortality rate. Nosocomial transmission may have accounted for approximately half of all cases during the first wave of the pandemic.
Aims. Postoperative delirium (POD) and postoperative cognitive decline (POCD) are common surgical complications. In the UK, the Best Practice Tariff incentivizes the screening of delirium in patients with hip fracture. Further, a National Hip Fracture Database (NHFD) performance indicator is the reduction in the incidence of POD. To aid in its recognition, we sought to determine factors associated with POD and POCD in patients with hip fractures. Methods. We interrogated the NHFD data on patients presenting with hip fractures to our institution from 2016 to 2018. POD was determined using the 4AT score, as recommended by the NHFD and UK Department of Health. POCD was defined as a decline in Abbreviated Mental Test Score (AMTS) of two or greater. Using logistic regression, we adjusted for covariates to identify factors associated with POD and POCD. Results. Of the 1,224 patients presenting in the study period, 1,023 had complete datasets for final analysis. POD was observed in 242 patients (25%). On multivariate analysis only preoperative AMTS and American Society of Anesthesiologists grade (ASA) were independent predictors of POD. Every point increase in AMTS was associated with a fall in the odds of POD by a factor of 0.60 (95% confidence interval (CI) 0.56 to 0.63, p < 0.001). Every grade increase in ASA led to a 1.7-fold increase in the odds of POD (95% CI 1.13 to 2.50, p = 0.009). A preoperative AMTS of less than 8 was strongly predictive of POD with area under the receiver operating characteristic of 0.86 (95% CI 0.84 to 0.89). Only ASA was predictive of POCD—every grade increase in ASA led to a 2.6-fold increase in the odds of POCD (95% CI 1.7 to 4.0, p < 0.001). Conclusion. POD and POCD are common in the hip fracture patients. Preoperative AMTS and ASA are strong predictors of POD, and ASA predictive of POCD. This may aid in the earlier
Aims. Several radiological methods of measuring anteversion of the acetabular component after total hip arthroplasty (THA) have been described. These are limited by low reproducibility, are less accurate than CT 3D reconstruction, and are cumbersome to use. These methods also partly rely on the
Background. The Comprehensive Care for Joint Replacement (CJR) model was implemented in April-2016 to standardize cost and improve quality of care for two of the most commonly billed inpatient procedures for Medicare patients, total knee and total hip arthroplasty. The purpose of this study is to compare one institution's predicted savings and losses under the CJR model with actual savings and losses after two years of implementation and discuss new methods to maintain savings. Methods. Using our institution's data, we calculated the mean cost per episode of care. We calculated the percent reduction in target price and percent savings or losses per case for the CJR and Bundle Payment Care Initiative (BPCI) for each Medicare Severity Diagnosis Related Group (MS-DRG) using mean cost per episode and CJR and BPCI target prices. We compared the target prices, annual savings, and losses per episode of care for both CJR and BPCI. All CJR savings, projected and actual, were computed by comparing CJR savings to that of 2018 BPCI savings. Results. We found an average savings of 2.32% under CJR compared to the projected loss of −11.6% for MS-DRG 469 with fracture. There was a 7.97% savings for MS-DRG 470 without fracture compared to the projected 1.9%, a 20.94% savings for MS-DRG 470 with fracture compared to the projected 23.7%, and a loss of −3.98% for MS-DRG 469 without fracture compared to the projected 2.5% savings. Conclusions. The CJR target prices are lower than that of BPCI and this makes maintaining an episode of care at or below the target price increasingly difficult. Discharge disposition and readmission are well established factors that increase hospital cost [7]. However, reduction of these does not seem enough to maintain savings under the CJR model. New cost savings mechanisms such as
Introduction. Patients with reduced lumbar spine mobility are at higher risk of dislocation after THA as their hips have to compensate for spinal stiffness. Therefore our study aimed to 1) Define the optimal protocol for identifying patients with mobile hips and stiff lumbar spines and 2) Determine clinical and standing radiographic parameters predicting high hip and reduced lumbar spine mobility. Methods. This prospective diagnostic cohort study followed 113 consecutive patients with end-stage hip osteoarthritis (OA) awaiting THA. Radiographic measurements were performed for the lumbar lordosis angle, pelvic tilt and pelvic-femoral angle on lateral radiographs in the standing, ‘relaxed-seated’ and ‘deep-seated’ (i.e. torso maximally leaning forward) position. A “hip user index” was calculated in order to quantify the contribution of the hip joint to the overall sagittal movement performed by the femur, pelvis and lumbar spine. Results. Radiographs in the relaxed-seated position had an accuracy of 56% (95%CI:46–65%) to detect patients with stiff lumbar spines, compared to a detected rate of 100% in the deep-seated position. The mean ‘hip user index’ was 63±12% and ten patients (9%) were hip users, having an index of 80% or more. A standing pelvic tilt of ≥18.5° was the only predictor for being a hip user with a sensitivity of 90% and specificity of 71% (AUC 0.83). Patients with a standing pelvic tilt ≥18.5° and an unbalanced spine with a flatback deformity had a 30xfold relative risk (95%-CI:4–226; p<0.001) of being a hip user. Conclusion. Patients awaiting THA and having high hip and reduced lumbar spine mobility can be screened for with lateral standing radiographs of the spinopelvic complex and a thorough clinical examination. If the initial screening is positive, radiographs in the deep-seated position allow for better
In this study, we aimed to visualize the spatial distribution characteristics of femoral head necrosis using a novel measurement method. We retrospectively collected CT imaging data of 108 hips with non-traumatic osteonecrosis of the femoral head from 76 consecutive patients (mean age 34.3 years (SD 8.1), 56.58% male (n = 43)) in two clinical centres. The femoral head was divided into 288 standard units (based on the orientation of units within the femoral head, designated as N[Superior], S[Inferior], E[Anterior], and W[Posterior]) using a new measurement system called the longitude and latitude division system (LLDS). A computer-aided design (CAD) measurement tool was also developed to visualize the measurement of the spatial location of necrotic lesions in CT images. Two orthopaedic surgeons independently performed measurements, and the results were used to draw 2D and 3D heat maps of spatial distribution of necrotic lesions in the femoral head, and for statistical analysis.Aims
Methods
Background. Postoperative recovery after routine total hip arthroplasty (THA) can lead to the development of prolonged opioid use but there are few tools for predicting this adverse outcome. The purpose of this study was to develop machine learning algorithms for preoperative prediction of prolonged post-operative opioid use after THA. Methods. A retrospective review of electronic health records was conducted at two academic medical centers and three community hospitals to identify adult patients who underwent THA for osteoarthritis between January 1. st. , 2000 and August 1. st. , 2018. Prolonged postoperative opioid prescriptions were defined as continuous opioid prescriptions after surgery to at least 90 days after surgery. Five machine learning algorithms were developed to predict this outcome and were assessed by discrimination, calibration, and decision curve analysis. Results. Overall, 5507 patients underwent THA, of which 345 (6.3%) had prolonged postoperative opioid prescriptions. The factors determined for prediction of prolonged postoperative opioid prescriptions were: age, duration of pre-operative opioid exposure, preoperative hemoglobin, and certain preoperative medications (anti-depressants, benzodiazepines, non-steroidal anti-inflammatory drugs, and beta-2-agonists). The elastic-net penalized logistic regression model achieved the best performance across discrimination (c-statistic = 0.77), calibration, and decision curve analysis. This model was incorporated into a digital application able to provide both predictions and explanations; available here: . https://sorg-apps.shinyapps.io/thaopioid/. Conclusion. If externally validated in independent populations, the algorithms developed in this study could improve preoperative screening and support for THA patients at high-risk for prolonged postoperative opioid use. Early
