Aims. To develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials. Methods. This study included 2,388 patients from the HEALTH and FAITH trials, with 90-day and one-year mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without), calibration (observed outcome compared to the predicted probability), and the Brier score (composite of discrimination and calibration). Results. The developed algorithms distinguished between patients at high and low risk for 90-day and one-year mortality. The penalized logistic regression algorithm had the best performance metrics for both 90-day (c-statistic 0.80, calibration slope 0.95, calibration intercept -0.06, and Brier score 0.039) and one-year (c-statistic 0.76, calibration slope 0.86, calibration intercept -0.20, and Brier score 0.074) mortality prediction in the hold-out set. Conclusion. Using high-quality data, the ML-based prediction models accurately predicted 90-day and one-year mortality in patients aged 50 years or older with a FNF. The final models must be externally validated to assess generalizability to other populations, and prospectively evaluated in the process of shared decision-making. Cite this article: Bone Jt Open 2023;4(3):168–181

Aims. This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model. Methods. The study included 538 joints that underwent primary THA. The patients were divided into groups using unsupervised time series clustering for five-year BMD loss of Gruen zone 7 postoperatively, and a machine-learning model to predict the BMD loss was developed. Additionally, the predictor for BMD loss was extracted using SHapley Additive exPlanations (SHAP). The patient-specific efficacy of bisphosphonate, which is the most important categorical predictor for BMD loss, was examined by calculating the change in predictive probability when hypothetically switching between the inclusion and exclusion of bisphosphonate. Results. Time series clustering allowed us to divide the patients into two groups, and the predictive factors were identified including patient- and operation-related factors. The area under the receiver operating characteristic (ROC) curve (AUC) for the BMD loss prediction averaged 0.734. Virtual administration of bisphosphonate showed on average 14% efficacy in preventing BMD loss of zone 7. Additionally, stem types and preoperative triglyceride (TG), creatinine (Cr), estimated glomerular filtration rate (eGFR), and creatine kinase (CK) showed significant association with the estimated patient-specific efficacy of bisphosphonate. Conclusion. Periprosthetic BMD loss after THA is predictable based on patient- and operation-related factors, and optimal prescription of bisphosphonate based on the prediction may prevent BMD loss. Cite this article: Bone Joint Res 2024;13(4):184–192

Aims. The aim of this study was to evaluate the reliability and validity of a patient-specific algorithm which we developed for predicting changes in sagittal pelvic tilt after total hip arthroplasty (THA). Methods. This retrospective study included 143 patients who underwent 171 THAs between April 2019 and October 2020 and had full-body lateral radiographs preoperatively and at one year postoperatively. We measured the pelvic incidence (PI), the sagittal vertical axis (SVA), pelvic tilt, sacral slope (SS), lumbar lordosis (LL), and thoracic kyphosis to classify patients into types A, B1, B2, B3, and C. The change of pelvic tilt was predicted according to the normal range of SVA (0 mm to 50 mm) for types A, B1, B2, and B3, and based on the absolute value of one-third of the PI-LL mismatch for type C patients. The reliability of the classification of the patients and the prediction of the change of pelvic tilt were assessed using kappa values and intraclass correlation coefficients (ICCs), respectively. Validity was assessed using the overall mean error and mean absolute error (MAE) for the prediction of the change of pelvic tilt. Results. The kappa values were 0.927 (95% confidence interval (CI) 0.861 to 0.992) and 0.945 (95% CI 0.903 to 0.988) for the inter- and intraobserver reliabilities, respectively, and the ICCs ranged from 0.919 to 0.997. The overall mean error and MAE for the prediction of the change of pelvic tilt were -0.3° (SD 3.6°) and 2.8° (SD 2.4°), respectively. The overall absolute change of pelvic tilt was 5.0° (SD 4.1°). Pre- and postoperative values and changes in pelvic tilt, SVA, SS, and LL varied significantly among the five types of patient. Conclusion. We found that the proposed algorithm was reliable and valid for predicting the standing pelvic tilt after THA. Cite this article: Bone Joint J 2024;106-B(1):19–27

Aims. To develop and externally validate a parsimonious statistical prediction model of 90-day mortality after elective total hip arthroplasty (THA), and to provide a web calculator for clinical usage. Methods. We included 53,099 patients with cemented THA due to osteoarthritis from the Swedish Hip Arthroplasty Registry for model derivation and internal validation, as well as 125,428 patients from England and Wales recorded in the National Joint Register for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey (NJR) for external model validation. A model was developed using a bootstrap ranking procedure with a least absolute shrinkage and selection operator (LASSO) logistic regression model combined with piecewise linear regression. Discriminative ability was evaluated by the area under the receiver operating characteristic curve (AUC). Calibration belt plots were used to assess model calibration. Results. A main effects model combining age, sex, American Society for Anesthesiologists (ASA) class, the presence of cancer, diseases of the central nervous system, kidney disease, and diagnosed obesity had good discrimination, both internally (AUC = 0.78, 95% confidence interval (CI) 0.75 to 0.81) and externally (AUC = 0.75, 95% CI 0.73 to 0.76). This model was superior to traditional models based on the Charlson (AUC = 0.66, 95% CI 0.62 to 0.70) and Elixhauser (AUC = 0.64, 95% CI 0.59 to 0.68) comorbidity indices. The model was well calibrated for predicted probabilities up to 5%. Conclusion. We developed a parsimonious model that may facilitate individualized risk assessment prior to one of the most common surgical interventions. We have published a web calculator to aid clinical decision-making. Cite this article: Bone Joint J 2021;103-B(3):469–478

Aims

Our aim was to examine the Elixhauser and Charlson comorbidity indices, based on administrative data available before surgery, and to establish their predictive value for mortality for patients who underwent hip arthroplasty in the management of a femoral neck fracture.

We have studied the correlation between the prevention of progressive collapse and the ratio of the intact articular surface of the femoral head, after transtrochanteric rotational osteotomy for osteonecrosis. We used probit analysis on 125 hips in order to assess the ratio necessary to prevent progressive radiological collapse over a ten-year period. The results show that a minimum postoperative intact ratio of 34% was required. This critical ratio may be useful for surgical planning and in assessing the natural history of the condition.

We report the ten-year results for three designs of stem in 240 total hip replacements, for which subsidence had been measured on plain radiographs at regular intervals. Accurate migration patterns could be determined by the method of Einzel-Bild-Roentgen-Analyse-femoral component analysis (EBRA-FCA) for 158 hips (66%).

Of these, 108 stems (68%) remained stable throughout, and five (3%) started to migrate after a median of 54 months. Initial migration of at least 1 mm was seen in 45 stems (29%) during the first two years, but these then became stable. We revised 17 stems for aseptic loosening, and 12 for other reasons. Revision for aseptic loosening could be predicted by EBRA-FCA with a sensitivity of 69%, a specificity of 80%, and an accuracy of 79% by the use of a threshold of subsidence of 1.5 mm during the first two years. Similar observations over a five-year period allowed the long-term outcome to be predicted with an accuracy of 91%.

We discuss the importance of four different patterns of subsidence and confirm that the early measurement of migration by a reasonably accurate method can help to predict long-term outcome. Such methods should be used to evaluate new and modified designs of prosthesis.

Aims. Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. Methods. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy. Results. We identified nine predictors from an analysis of baseline spinopelvic characteristics and surgical planning parameters. Using fivefold cross-validation, the LGBM achieved 70.2% impingement prediction accuracy. With impingement data, the LGBM estimated direction with 85% accuracy, while the support vector machine (SVM) determined impingement type with 72.9% accuracy. After integrating imaging data with a multilayer perceptron (tabular) and a convolutional neural network (radiograph), the LGBM’s prediction was 68.1%. Both combined and LGBM-only had similar impingement direction prediction rates (around 84.5%). Conclusion. This study is a pioneering effort in leveraging AI for impingement prediction in THA, utilizing a comprehensive, real-world clinical dataset. Our machine-learning algorithm demonstrated promising accuracy in predicting impingement, its type, and direction. While the addition of imaging data to our deep-learning algorithm did not boost accuracy, the potential for refined annotations, such as landmark markings, offers avenues for future enhancement. Prior to clinical integration, external validation and larger-scale testing of this algorithm are essential. Cite this article: Bone Jt Open 2024;5(8):671–680

Aims. Better prediction of outcome after total hip arthroplasty (THA) is warranted. Systemic inflammation and central neuroinflammation are possibly involved in progression of osteoarthritis and pain. We explored whether inflammatory biomarkers in blood and cerebrospinal fluid (CSF) were associated with clinical outcome, and baseline pain or disability, 12 months after THA. Methods. A total of 50 patients from the Danish Pain Research Biobank (DANPAIN-Biobank) between January and June 2018 were included. Postoperative outcome was assessed as change in Oxford Hip Score (OHS) from baseline to 12 months after THA, pain was assessed on a numerical rating scale, and disability using the Pain Disability Index. Multiple regression models for each clinical outcome were included for biomarkers in blood and CSF, respectively, including age, sex, BMI, and Kellgren-Lawrence score. Results. Change in OHS was associated with blood concentrations of tumour necrosis factor (TNF), interleukin-8 (IL-8), interleukin-6 receptor (IL-6R), glycoprotein 130 (gp130), and IL-1β (R. 2. = 0.28, p = 0.006), but not with CSF biomarkers. Baseline pain was associated with blood concentrations of lymphotoxin alpha (LTα), TNFR1, TNFR2, and IL-6R (R. 2. = 0.37, p < 0.001) and CSF concentrations of TNFR1, TNFR2, IL-6, IL-6R, and IL-1Ra (R. 2. = 0.40, p = 0.001). Baseline disability was associated with blood concentrations of TNF, LTα, IL-8, IL-6, and IL-1α (R. 2. = 0.53, p < 0.001) and CSF concentrations of gp130, TNF, and IL-1β (R. 2. = 0.26, p = 0.002). Thus, preoperative systemic low-grade inflammation predicted 12-month postoperative outcome after THA, and was associated with preoperative pain and disability. Conclusion. This study highlights the importance of systemic inflammation in osteoarthritis, and presents a possible path for better patient selection for THA in the future. Preoperative central neuroinflammation was associated with preoperative pain and disability, but not change in OHS after THA. Cite this article: Bone Joint Res 2024;13(12):741–749

Aims. The aims of this study were to validate the Forgotten Joint Score-12 (FJS-12) in the postoperative evaluation of periacetabular osteotomy (PAO), identify factors associated with joint awareness after PAO, and determine the FJS-12 threshold for patient-acceptable symptom state (PASS). Methods. Data from 686 patients (882 hips) with hip dysplasia who underwent transposition osteotomy of the acetabulum, a type of PAO, between 1998 and 2019 were reviewed. After screening the study included 442 patients (582 hips; response rate, 78%). Patients who completed a study questionnaire consisting of the visual analogue scale (VAS) for pain and satisfaction, FJS-12, and Hip disability and Osteoarthritis Outcome Score (HOOS) were included. The ceiling effects, internal consistency, convergent validity, and PASS thresholds of FJS-12 were investigated. Results. The median follow-up was 12 years (interquartile range 7 to 16). The ceiling effect of FJS-12 was 7.2%, the lowest of all the measures examined. FJS-12 correlated with all HOOS subscales (ρ = 0.72 to 0.77, p < 0.001) and pain and satisfaction-VAS (ρ = -0.63 and 0.56, p < 0.001), suggesting good convergent validity. Cronbach’s α was 0.95 for the FJS-12, which indicated excellent internal consistency. The median FJS-12 score for preoperative Tönnis grade 0 hips (60 points) was higher than that for grade 1 (51 points) or 2 (46 points). When PASS was defined as pain-VAS < 21 and satisfaction-VAS ≥ 77, the FJS-12 threshold that maximized the sensitivity and specificity for detecting PASS was 50 points (area under the curve (AUC) = 0.85). Conclusion. Our results suggest that FJS-12 is a valid and reliable assessment tool for patients undergoing PAO, and the threshold of 50 points may be useful to determine patient satisfaction following PAO in clinical settings. Further investigation of the factors influencing postoperative joint awareness may enable improved prediction of treatment efficacy and informed decision-making regarding the indication of PAO. Cite this article: Bone Joint J 2023;105-B(7):760–767

Aims. The lateral centre-edge angle (LCEA) is a plain radiological measure of superolateral cover of the femoral head. This study aims to establish the correlation between 2D radiological and 3D CT measurements of acetabular morphology, and to describe the relationship between LCEA and femoral head cover (FHC). Methods. This retrospective study included 353 periacetabular osteotomies (PAOs) performed between January 2014 and December 2017. Overall, 97 hips in 75 patients had 3D analysis by Clinical Graphics, giving measurements for LCEA, acetabular index (AI), and FHC. Roentgenographical LCEA, AI, posterior wall index (PWI), and anterior wall index (AWI) were measured from supine AP pelvis radiographs. The correlation between CT and roentgenographical measurements was calculated. Sequential multiple linear regression was performed to determine the relationship between roentgenographical measurements and CT FHC. Results. CT-measured LCEA and AI correlated strongly with roentgenographical LCEA (r = 0.92; p < 0.001) and AI (r = 0.83; p < 0.001). Radiological LCEA correlated very strongly with CT FHC (r = 0.92; p < 0.001). The sum of AWI and PWI also correlated strongly with CTFHC (r = 0.73; p < 0.001). CT measurements of LCEA and AI were 3.4° less and 2.3° greater than radiological LCEA and AI measures. There was a linear relation between radiological LCEA and CT FHC. The linear regression model statistically significantly predicted FHC from LCEA, F(1,96) = 545.1 (p < 0.001), adjusted R. 2. = 85.0%, with the prediction equation: CT FHC(%) = 42.1 + 0.77(XRLCEA). Conclusion. CT and roentgenographical measurement of acetabular parameters are comparable. Currently, a radiological LCEA greater than 25° is considered normal. This study demonstrates that those with hip pain and normal radiological acetabular parameters may still have deficiencies in FHC. More sophisticated imaging techniques such as 3D CT should be considered for those with hip pain to identify deficiencies in FHC. Cite this article: Bone Jt Open 2022;3(1):12–19

Aims. In computer simulations, the shape of the range of motion (ROM) of a stem with a cylindrical neck design will be a perfect cone. However, many modern stems have rectangular/oval-shaped necks. We hypothesized that the rectangular/oval stem neck will affect the shape of the ROM and the prosthetic impingement. Methods. Total hip arthroplasty (THA) motion while standing and sitting was simulated using a MATLAB model (one stem with a cylindrical neck and one stem with a rectangular neck). The primary predictor was the geometry of the neck (cylindrical vs rectangular) and the main outcome was the shape of ROM based on the prosthetic impingement between the neck and the liner. The secondary outcome was the difference in the ROM provided by each neck geometry and the effect of the pelvic tilt on this ROM. Multiple regression was used to analyze the data. Results. The stem with a rectangular neck has increased internal and external rotation with a quatrefoil cross-section compared to a cone in a cylindrical neck. Modification of the cup orientation and pelvic tilt affected the direction of projection of the cone or quatrefoil shape. The mean increase in internal rotation with a rectangular neck was 3.4° (0° to 7.9°; p < 0.001); for external rotation, it was 2.8° (0.5° to 7.8°; p < 0.001). Conclusion. Our study shows the importance of attention to femoral implant design for the assessment of prosthetic impingement. Any universal mathematical model or computer simulation that ignores each stem’s unique neck geometry will provide inaccurate predictions of prosthetic impingement. Cite this article: Bone Joint Res 2021;10(12):780–789

Aims

Hip arthroscopy (HA) has become the treatment of choice for femoroacetabular impingement (FAI). However, less favourable outcomes following arthroscopic surgery are expected in patients with severe chondral lesions. The aim of this study was to assess the outcomes of HA in patients with FAI and associated chondral lesions, classified according to the Outerbridge system.

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In this study, we aimed to visualize the spatial distribution characteristics of femoral head necrosis using a novel measurement method.

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Cemented hemiarthroplasty is an effective form of treatment for most patients with an intracapsular fracture of the hip. However, it remains unclear whether there are subgroups of patients who may benefit from the alternative operation of a modern uncemented hemiarthroplasty – the aim of this study was to investigate this issue. Knowledge about the heterogeneity of treatment effects is important for surgeons in order to target operations towards specific subgroups who would benefit the most.

Aims

The localization of necrotic areas has been reported to impact the prognosis and treatment strategy for osteonecrosis of the femoral head (ONFH). Anteroposterior localization of the necrotic area after a femoral neck fracture (FNF) has not been properly investigated. We hypothesize that the change of the weight loading direction on the femoral head due to residual posterior tilt caused by malunited FNF may affect the location of ONFH. We investigate the relationship between the posterior tilt angle (PTA) and anteroposterior localization of osteonecrosis using lateral hip radiographs.

Aims

It is important to analyze objectively the hammering sound in cup press-fit technique in total hip arthroplasty (THA) in order to better understand the change of the sound during impaction. We hypothesized that a specific characteristic would present in a hammering sound with successful fixation. We designed the study to quantitatively investigate the acoustic characteristics during cementless cup impaction in THA.

Aims

It is important to analyze objectively the hammering sound in cup press-fit technique in total hip arthroplasty (THA) in order to better understand the change of the sound during impaction. We hypothesized that a specific characteristic would present in a hammering sound with successful fixation. We designed the study to quantitatively investigate the acoustic characteristics during cementless cup impaction in THA.

Aims

The Birmingham Hip Resurfacing (BHR) was introduced in 1997 to address the needs of young active patients using a historically proven large-diameter metal-on-metal (MoM) bearing. A single designer surgeon’s consecutive series of 130 patients (144 hips) was previously reported at five and ten years, reporting three and ten failures, respectively. The aim of this study was to extend the follow-up of this original cohort at 25 years.

Patient safety is a critical issue in elective total joint replacement surgery. Identifying risk factors that might predict complications and intensive care unit (ICU) admission proves instrumental in reducing morbidity and mortality. The institution’s experience with risk stratification and pre-operative ICU triage has resulted in a reduction in unplanned ICU admissions and post-operative complications after total hip replacement. The application of the prediction tools to total knee replacement has proven less robust so far. This work also reviews areas for future research in patient safety and cost containment. . Cite this article: Bone Joint J 2013;95-B, Supple A:74–6