Aims. Hip arthroscopy has gained prominence as a primary surgical intervention for symptomatic femoroacetabular impingement (FAI). This study aimed to identify radiological features, and their combinations, that predict the outcome of hip arthroscopy for FAI. Methods. A prognostic cross-sectional cohort study was conducted involving patients from a single centre who underwent hip arthroscopy between January 2013 and April 2021. Radiological metrics measured on conventional radiographs and magnetic resonance arthrography were systematically assessed. The study analyzed the relationship between these metrics and complication rates, revision rates, and patient-reported outcomes. Results. Out of 810 identified hip arthroscopies, 359 hips were included in the study. Radiological risk factors associated with unsatisfactory outcomes after cam resection included a dysplastic posterior wall, Tönnis grade 2 or higher, and over-correction of the α angle. The presence of acetabular retroversion and dysplasia were also significant predictors for worse surgical outcomes. Notably, over-correction of both cam and pincer deformities resulted in poorer outcomes than under-correction. Conclusion. We recommend caution in performing hip arthroscopy in patients who have three positive acetabular retroversion signs. Acetabular dysplasia with a lateral centre-edge angle of less than 20° should not be treated with isolated hip arthroscopy. Acetabular rim-trimming should be avoided in patients with borderline dysplasia, and care should be taken to avoid over-correction of a cam deformity and/or pincer deformity. Cite this article: Bone Joint J 2024;106-B(8):775–782

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. Transfusion after primary total hip arthroplasty (THA) has become rare, and identification of causative factors allows preventive measures. The aim of this study was to determine patient-specific factors that increase the risk of needing a blood transfusion. Methods. All patients who underwent elective THA were analyzed retrospectively in this single-centre study from 2020 to 2021. A total of 2,892 patients were included. Transfusion-related parameters were evaluated. A multiple logistic regression was performed to determine whether age, BMI, American Society of Anesthesiologists (ASA) grade, sex, or preoperative haemoglobin (Hb) could predict the need for transfusion within the examined patient population. Results. The overall transfusion rate was 1.2%. Compared to the group of patients without blood transfusion, the transfused group was on average older (aged 73.8 years (SD 9.7) vs 68.6 years (SD 10.1); p = 0.020) and was mostly female (p = 0.003), but showed no significant differences in terms of BMI (28.3 kg/m. 2. (SD 5.9) vs 28.7 kg/m. 2. (SD 5.2); p = 0.720) or ASA grade (2.2 (SD 0.5) vs 2.1 (SD 0.4); p = 0.378). The regression model identified a cutoff Hb level of < 7.6 mmol/l (< 12.2 g/dl), aged > 73 years, and a BMI of 35.4 kg/m² or higher as the three most reliable predictors associated with postoperative transfusion in THA. Conclusion. The possibility of transfusion is predictable based on preoperatively available parameters. The proposed thresholds for preoperative Hb level, age, and BMI can help identify patients and take preventive measures if necessary. Cite this article: Bone Jt Open 2024;5(7):560–564

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. The aims of this study were to determine if an increasing serum cobalt (Co) and/or chromium (Cr) concentration is correlated with a decreasing Harris Hip Score (HHS) and Hip disability and Osteoarthritis Outcome Score (HOOS) in patients who received the Articular Surface Replacement (ASR) hip resurfacing arthroplasty (HRA), and to evaluate the ten-year revision rate and show if sex, inclination angle, and Co level influenced the revision rate. Methods. A total of 62 patients with an ASR-HRA were included and monitored yearly postoperatively. At follow-up, serum Co and Cr levels were measured and the HHS and the HOOS were scored. In addition, preoperative patient and implant variables and the need for revision surgery were recorded. We used a linear mixed model to relate the serum Co and Cr levels to different patient-reported outcome measures (PROMs). For the survival analyses we used the Kaplan-Meier and Cox regression model. Results. We found that an increase of one part per billion (ppb) in serum Co and Cr levels correlated significantly with worsening of the HHS in the following year. This significant correlation was also true for the HOOS-Pain and HOOS-quality of life sub scores. The overall ten-year survival rate in our cohort was 65% (95% confidence interval (CI) 52.5 to 77.6). Cox regression analysis showed a significant hazard ratio (HR) of 1.08 (95% CI 1.01 to 1.15; p = 0.028) for serum Co level. No significance was found with sex or inclination angle. Conclusion. This study shows that increasing serum Co and Cr levels measured in patients with an ASR-HRA are predictive for deterioration in HHS and HOOS subscales in the following year. Increasing serum Co and Cr should forewarn both surgeon and patient that there is a heightened risk of failure. Continued and regular review of patients with an ASR-HRA implant by measurement of serum Co/Cr levels and PROMs remains essential. Cite this article: Bone Joint J 2023;105-B(7):775–782

Identification of patients at risk of not achieving minimally clinically important differences (MCID) in patient reported outcome measures (PROMs) is important to ensure principled and informed pre-operative decision making. Machine learning techniques may enable the generation of a predictive model for attainment of MCID in hip arthroscopy. Aims: 1) to determine whether machine learning techniques could predict which patients will achieve MCID in the iHOT-12 PROM 6 months after arthroscopic management of femoroacetabular impingement (FAI), 2) to determine which factors contribute to their predictive power. Data from the UK Non-Arthroplasty Hip Registry database was utilised. We identified 1917 patients who had undergone hip arthroscopy for FAI with both baseline and 6 month follow up iHOT-12 and baseline EQ-5D scores. We trained three established machine learning algorithms on our dataset to predict an outcome of iHOT-12 MCID improvement at 6 months given baseline characteristics including demographic factors, disease characteristics and PROMs. Performance was assessed using area under the receiver operating characteristic (AUROC) statistics with 5-fold cross validation. The three machine learning algorithms showed quite different performance. The linear logistic regression model achieved AUROC = 0.59, the deep neural network achieved AUROC = 0.82, while a random forest model had the best predictive performance with AUROC 0.87. Of demographic factors, we found that BMI and age were key predictors for this model. We also found that removing all features except baseline responses to the iHOT-12 questionnaire had little effect on performance for the random forest model (AUROC = 0.85). Disease characteristics had little effect on model performance. Machine learning models are able to predict with good accuracy 6-month post-operative MCID attainment in patients undergoing arthroscopic management for FAI. Baseline scores from the iHOT-12 questionnaire are sufficient to predict with good accuracy whether a patient is likely to reach MCID in post-operative PROMs

Short cementless femoral stems are increasingly popular as they allow for less dissection for insertion. Use of such stems with the anterior approach (AA) may be associated with considerable per-operative fracture risk. This study's primary aim was to evaluate whether patient-specific femoral- and pelvic- morphology and surgical technique, influence per-operative fracture risk. In doing so, we aimed to describe important anatomical thresholds alerting surgeons. This is a single-centre, multi-surgeon retrospective, case-control matched study. Of 1145 primary THAs with a short, cementless stem inserted via the AA, 39 periprosthetic fractures (3.4%) were identified. These were matched for factors known to increase fracture risk (age, gender, BMI, side, Dorr classification, stem offset and indication for surgery) with 78 THAs that did not sustain a fracture. Radiographic analysis was performed using validated software to measure femoral- (canal flare index [CFI], morphological cortical index [MCI], calcar-calcar ratio [CCR]) and pelvic- (Ilium-ischial ratio [IIR], ilium overhang, and ASIS to greater trochanter distance) morphologies and surgical technique (% canal fill). Multivariate and Receiver-Operator Curve (ROC) analysis was performed to identify predictors of fracture. Femoral factors that differed included CFI (3.7±0.6 vs 2.9±0.4, p<0.001) and CCR (0.5±0.1 vs 0.4±0.1, p=0.006). The mean IIR was higher in fracture cases (3.3±0.6 vs 3.0±0.5, p<0.001). % Canal fill was reduced in fracture cases (82.8±7.6 vs 86.7±6.8, p=0.007). Multivariate analysis and ROC analyses revealed a threshold CFI of 3.17 was predictive of fracture (sensitivity:84.6% / specificity:75.6%). Fracture risk was 29 times higher when patients had CFI>3.17 and II ratio>3 (OR:29.2 95%CI: 9.5–89.9, p<0.001). Patient-specific anatomical parameters are important predictors of fracture-risk. When considering the use of short stems via the AA, careful radiographic analysis would help identify those at risk in order to consider alternative stem options

Aims. Hip fractures are some of the most common fractures encountered in orthopaedic practice. We aimed to identify whether perioperative hypotension is a predictor of 30-day mortality, and to stratify patient groups that would benefit from closer monitoring and early intervention. While there is literature on intraoperative blood pressure, there are limited studies examining pre- and postoperative blood pressure. Methods. We conducted a prospective observational cohort study over a one-year period from December 2021 to December 2022. Patient demographic details, biochemical results, and haemodynamic observations were taken from electronic medical records. Statistical analysis was conducted with the Cox proportional hazards model, and the effects of independent variables estimated with the Wald statistic. Kaplan-Meier survival curves were estimated with the log-rank test. Results. A total of 528 patients were identified as suitable for inclusion. On multivariate analysis, postoperative hypotension of a systolic blood pressure (SBP) < 90 mmHg two to 24 hours after surgery showed an increased hazard ratio (HR) for 30-day mortality (HR 4.6 (95% confidence interval (CI) 2.3 to 8.9); p < 0.001) and was an independent risk factor accounting for sex (HR 2.7 (95% CI 1.4 to 5.2); p = 0.003), age (HR 1.1 (95% CI 1.0 to 1.1); p = 0.016), American Society of Anesthesiologists grade (HR 2.7 (95% CI 1.5 to 4.6); p < 0.001), time to theatre > 24 hours (HR 2.1 (95% CI 1.1 to 4.2); p = 0.025), and preoperative anaemia (HR 2.3 (95% CI 1.0 to 5.2); p = 0.043). A preoperative SBP of < 120 mmHg was close to achieving significance (HR 1.9 (95% CI 0.99 to 3.6); p = 0.052). Conclusion. Our study is the first to demonstrate that postoperative hypotension within the first 24 hours is an independent risk factor for 30-day mortality after hip fracture surgery. Clinicians should recognize patients who have a SBP of < 90 mmHg in the early postoperative period, and be aware of the increased mortality risk in this specific cohort who may benefit from a closer level of monitoring and early intervention. Cite this article: Bone Joint J 2024;106-B(2):189–194

It is anecdotally thought that a good outcome from the first of staged total hip arthroplasties (THAs) is predictive of benefit on the contralateral side. The objective was to determine whether outcome from the first THA could be used to predict outcome from the second, contralateral THA. A retrospective cohort study of consecutive patients undergoing staged THAs at a UK arthroplasty centre over 25-years (1995–2020). A control THA group was identified and matched for age, gender, BMI, implant and diagnosis. One-year patient-reported outcome data was available for 91% 1543/1700. 1700 patients who underwent staged THA were compared to 1700 matched controls. Preoperative status was comparable for pain, function, and modified Harris hip score (mHHS, mean 41 SD 13 for both groups). At one year, there was a 2% dissatisfaction rate in all groups (first of staged THAs, second of staged THAs and controls). Groups were similar in terms of pain, function and mHHS (mean 88 SD 11 for all groups). For every 100 patients undergoing staged THAs, 87 had a bilateral good outcome (mHHS >70 both), 11 had unilateral poor outcome (mHHS >70 one, <70 other) and 2 had bilateral poor outcome (mHHS <70 both). If the first THA had a good outcome, the relative risk of a bad outcome was 20% less than for controls (RR 0.8 95% CI 0.6–1.1). If the first THA had a poor outcome, the risk of a second poor outcome was 4.5 times higher (RR 4.5 95% CI 3.2–6.4), increasing from 6% to 29% (absolute risk). Patients undergoing staged THAs with a good outcome from the first THA were less likely to have a bad outcome with the second. Risk of a poor outcome after a previous successful THA was 6% but rose to almost 30% with a previous poor outcome. This remained after correcting for patient variables including gender, age, BMI and diagnosis, indicating a potentially novel independent risk factor for poor outcome from staged THA

Aims. This study of patients with osteoarthritis (OA) of the hip aimed to: 1) characterize the contribution of the hip, spinopelvic complex, and lumbar spine when moving from the standing to the sitting position; 2) assess whether abnormal spinopelvic mobility is associated with worse symptoms; and 3) identify whether spinopelvic mobility can be predicted from static anatomical radiological parameters. Patients and Methods. A total of 122 patients with end-stage OA of the hip awaiting total hip arthroplasty (THA) were prospectively studied. Patient-reported outcome measures (PROMs; Oxford Hip Score, Oswestry Disability Index, and Veterans RAND 12-Item Health Survey Score) and clinical data were collected. Sagittal spinopelvic mobility was calculated as the change from the standing to sitting position using the lumbar lordosis angle (LL), sacral slope (SS), pelvic tilt (PT), pelvic-femoral angle (PFA), and acetabular anteinclination (AI) from lateral radiographs. The interaction of the different parameters was assessed. PROMs were compared between patients with normal spinopelvic mobility (10° ≤ ∆PT ≤ 30°) or abnormal spinopelvic mobility (stiff: ∆PT < ± 10°; hypermobile: ∆PT > ± 30°). Multiple regression and receiver operating characteristic (ROC) curve analyses were used to test for possible predictors of spinopelvic mobility. Results. Standing to sitting, the hip flexed by a mean of 57° (. sd. 17°), the pelvis tilted backwards by a mean of 20° (. sd. 12°), and the lumbar spine flexed by a mean of 20° (. sd. 14°); strong correlations were detected. There was no difference in PROMs between patients in the different spinopelvic mobility groups. Maximum hip flexion, standing PT, and standing AI were independent predictors of spinopelvic mobility (R. 2. = 0.42). The combined thresholds for standing was PT ≥ 13° and hip flexion ≥ 88° in the clinical examination, and had 90% sensitivity and 63% specificity of predicting spinopelvic stiffness, while SS ≥ 42° had 84% sensitivity and 67% specificity of predicting spinopelvic hypermobility. Conclusion. The hip, on average, accounts for three-quarters of the standing-to-sitting movement, but there is great variation. Abnormal spinopelvic mobility cannot be screened with PROMs. However, clinical and standing radiological features can predict spinopelvic mobility with good enough accuracy, allowing them to be used as reliable screening tools. Cite this article: Bone Joint J 2019;101-B:902–909

Aims. A proximal femur fracture (PFF) is a common orthopaedic presentation, with an incidence of over 25,000 cases reported in the Australian and New Zealand Hip Fracture Registry (ANZHFR) in 2018. Hip fractures are known to have high mortality. The purpose of this study was to determine the utility of the Clinical Frailty Scale (CFS) in predicting 30-day and one-year mortality after a PFF in older patients. Methods. A retrospective review of all fragility hip fractures who met the inclusion/exclusion criteria of the ANZHFR between 2017 and 2018 was undertaken at a single large volume tertiary hospital. There were 509 patients included in the study with one-year follow-up obtained in 502 cases. The CFS was applied retrospectively to patients according to their documented pre-morbid function and patients were stratified into five groups according to their frailty score. The groups were compared using t-test, analysis of variance (ANOVA), and the chi-squared test. The discriminative ability of the CFS to predict mortality was then compared with American Society of Anaesthesiologists (ASA) classification and the patient’s chronological age. Results. A total of 38 patients were deceased at 30 days and 135 patients at one year. The 30-day mortality rate increased from 1.3% (CFS 1 to 3; 1/80) to 14.6% (CFS ≥ 7; 22/151), and the one-year mortality increased from 3.8% (CFS 1 to 3; 3/80) to 41.7% (CFS ≥ 7; 63/151). The CFS was demonstrated superior discriminative ability in predicting mortality after PFF (area under the curve (AUC) 0.699; 95% confidence interval (CI) 0.651 to 0.747) when compared with the ASA (AUC 0.634; 95% CI 0.576 to 0.691) and chronological age groups (AUC 0.585; 95% CI 0.523 to 0.648). Conclusion. The CFS demonstrated utility in predicting mortality after PFF fracture. The CFS can be easily performed by non-geriatricians and may help to reduce age related bias influencing surgical decision making. Cite this article: Bone Joint Open 2020;1-8:443–449

It is unclear whether patients with early radiographic osteoarthritis (OA) but severe hip symptoms benefit from total hip replacement (THR). We aimed to assess which factors were associated with successful THR in this patient group. From a consecutive series of 1,935 patients undergoing THR we identified 70 (3.6%) patients with early OA (Kellgren and Lawrence (KL) grades 0-2). These were compared with 200 patients with advanced OA (KL grades 3–4). Outcomes were Oxford Hip Scores (OHS), EQ5D and EQ-VAS scores; compared pre-operatively with one year post-operatively. We investigated which clinical and radiographic (plain x-ray, CT, MRI) features predicted successful THR in the early OA group. Success was defined as reaching a postoperative OHS≥42. The early OA group were significantly younger (61 vs 66 years; P=0.0035). There were no significant differences in body mass index, ASA grade or gender. After adjusting for confounders, the advanced OA group had a significantly greater percentage of possible change (PoPC) in OHS (75.8% versus 50.4%; P<0.0001) and improvement in EQ5D (0.151 versus 0.002; P<0.0001). There were no significant differences in complication, revision or readmission rates. In the early OA group, we identified 16/70 (22.9%) patients who had a ‘successful’ THR. Of those with early OA, 38 patients had pre-operative CT or MRI scans. Patients who had a ‘successful’ THR were significantly more likely to have subchondral cysts on CT/MRI (91.7% versus 57.7%; P=0.0362). The presence of cysts on CT/MRI was associated with a significantly greater PoPC in OHS (61.6% versus 38.2%; P=0.0353). The combination of cysts and joint space width (JSW) <1mm was associated with a PoPC of 68%. Plain radiographs were found to significantly underestimate the narrowest JSW compared to CT/MRI (2.4mm versus 1.0mm; P<0.0001). We advise caution in performing THRs in patients with early OA (KL grades 0-2) on plain radiographs. We advocate pre-operative cross-sectional imaging (CT or MRI) in these patients. In the absence of cysts on cross-sectional imaging, a THR seems unlikely to provide a satisfactory outcome

Aims. Rotational acetabular osteotomy (RAO) has been reported to be effective in improving symptoms and preventing osteoarthritis (OA) progression in patients with mild to severe develomental dysplasia of the hip (DDH). However, some patients develop secondary OA even when the preoperative joint space is normal; determining who will progress to OA is difficult. We evaluated whether the preoperative cartilage condition may predict OA progression following surgery using T2 mapping MRI. Methods. We reviewed 61 hips with early-stage OA in 61 patients who underwent RAO for DDH. They underwent preoperative and five-year postoperative radiological analysis of the hip. Those with a joint space narrowing of more than 1 mm were considered to have 'OA progression'. Preoperative assessment of articular cartilage was also performed using 3T MRI with the T2 mapping technique. The region of interest was defined as the weightbearing portion of the acetabulum and femoral head. Results. There were 16 patients with postoperative OA progression. The T2 values of the centre to the anterolateral region of the acetabulum and femoral head in the OA progression cases were significantly higher than those in patients without OA progression. The preoperative T2 values in those regions were positively correlated with the narrowed joint space width. The receiver operating characteristic analysis revealed that the T2 value of the central portion in the acetabulum provided excellent discrimination, with OA progression patients having an area under the curve of 0.858. Furthermore, logistic regression analysis showed T2 values of the centre to the acetabulum’s anterolateral portion as independent predictors of subsequent OA progression (p < 0.001). Conclusion. This was the first study to evaluate the relationship between intra-articular degeneration using T2 mapping MRI and postoperative OA progression. Our findings suggest that preoperative T2 values of the hip can be better prognostic factors for OA progression than radiological measures following RAO. Cite this article: Bone Joint J 2021;103-B(9):1472–1478

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. 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. Patients and Methods. We analyzed data from 42 354 patients from the Swedish Hip Arthroplasty Register between 2005 and 2012. Only the first operated hip was included for patients with bilateral arthroplasty. We obtained comorbidity data by linkage from the Swedish National Patient Register, as well as death dates from the national population register. We used univariable Cox regression models to predict mortality based on the comorbidity indices, as well as multivariable regression with age and gender. Predictive power was evaluated by a concordance index, ranging from 0.5 to 1 (with the higher value being the better predictive power). A concordance index less than 0.7 was considered poor. We used bootstrapping for internal validation of the results. Results. The predictive power of mortality was poor for both the Elixhauser and Charlson comorbidity indices (concordance indices less than 0.7). The Charlson Comorbidity Index was superior to Elixhauser, and a model with age and gender was superior to both indices. Conclusion. Preoperative comorbidity from administrative data did not predict mortality for patients with a hip fracture treated by arthroplasty. This was true even if association on group level existed

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 identification of those selected to undergo THA. This likely relates to the complexity and heterogeneity of free-text information and the way that patients are determined to be surgical candidates

Aims. A borderline dysplastic hip can behave as either stable or unstable and this makes surgical decision making challenging. While an unstable hip may be best treated by acetabular reorientation, stable hips can be treated arthroscopically. Several imaging parameters can help to identify the appropriate treatment, including the Femoro-Epiphyseal Acetabular Roof (FEAR) index, measured on plain radiographs. The aim of this study was to assess the reliability and the sensitivity of FEAR index on MRI compared with its radiological measurement. Patients and Methods. The technique of measuring the FEAR index on MRI was defined and its reliability validated. A retrospective study assessed three groups of 20 patients: an unstable group of ‘borderline dysplastic hips’ with lateral centre edge angle (LCEA) less than 25° treated successfully by periacetabular osteotomy; a stable group of ‘borderline dysplastic hips’ with LCEA less than 25° treated successfully by impingement surgery; and an asymptomatic control group with LCEA between 25° and 35°. The following measurements were performed on both standardized radiographs and on MRI: LCEA, acetabular index, femoral anteversion, and FEAR index. Results. The FEAR index showed excellent intraobserver and interobserver reliability on both MRI and radiographs. The FEAR index was more reliable on radiographs than on MRI. The FEAR index on MRI was lower in the stable borderline group (mean -4.2° (. sd. 9.1°)) compared with the unstable borderline group (mean 7.9° (. sd. 6.8°)). With a FEAR index cut-off value of 2°, 90% of patients were correctly identified as stable or unstable using the radiological FEAR index, compared with 82.5% using the FEAR index on MRI. The FEAR index was a better predictor of instability on plain radiographs than on MRI. Conclusion. The FEAR index measured on MRI is less reliable and less sensitive than the FEAR index measured on radiographs. The cut-off value of 2° for radiological FEAR index predicted hip stability with 90% probability. Cite this article: Bone Joint J 2019;101-B:1578–1584

Background. Structural bone allografts are an established treatment method for long-bone structural defects arising from such conditions as trauma, sarcoma, and osteolysis following total joint replacement. However, the quality of structural bone allografts is difficult to non-destructively assess prior to use. The functional lifetime of structural allografts depend on their ability to resist cyclic loading, which can lead to fracture even at stress levels well below the yield strength. Because allograft bone has limited capacity for remodeling, optimizing allograft selection for bone quality could decrease long-term fracture risk. Raman spectroscopy biomarkers can non-destructively assess the three primary components of bone (collagen, mineral, and water), and may predict the resistance of donor bone allografts to fracture from cyclic loads. The purpose of this study was to prospectively assess the ability of Raman biomarkers to predict number of cycles to fracture (“cyclic fatigue life”) of human allograft cortical bone. Methods. Twenty-one cortical bone specimens were from the mid-diaphysis of human donor bone tissue (bilateral femurs from 4 donors: 63M, 61M, 51F, 48F) obtained from the Musculoskeletal Transplant Foundation. Six Raman biomarkers were analyzed: collagen disorganization, type B carbonate substitution (a surrogate for mineral maturation), matrix mineralization, and 3 water compartments. Specimens underwent cyclic fatigue testing under fully reversed conditions at 35 and 45MPa (physiologically relevant stress levels for structural allografts). Specimens were tested to fracture or to 30 million cycles (“run-out”), simulating 15 years of moderate activity (i.e., 6000 steps per day). Multivariate regression analysis was performed using a tobit model (censored linear regression) for prediction of cyclic fatigue life. Specimens were right-censored at 30 million cycles. Results. All of the 6 biomarkers that were evaluated were independently associated with cyclic fatigue life (p < 0.05). The multivariate model explained 70% of the variance in cyclic fatigue life (R2=0.695, p<0.001,). Increasing disordered collagen (p<0.001) and loosely collagen-bound water compartments (p<0.001) were associated with decreased cyclic fatigue life. Increasing type B carbonate substitution (p<0.001), matrix mineralization (p<0.001), tightly collagen-bound water (p<0.001), and mineral-bound water (p=0.002) were associated with increased cyclic fatigue life. In the predictive model, 42% of variance in cyclic fatigue life was attributable to degree of collagen disorder, all bound water compartments accounted for 6%, and age and sex accounted for 17%. Conclusions. Raman biomarkers of three bone components (collagen, mineral, and water) predict cyclic fatigue life of human cortical bone. Increased baseline collagen disorder was associated with decreased cyclic fatigue life, and was the strongest determinant of cyclic fatigue life. Increased matrix mineralization and mineral maturation were associated with increased cyclic fatigue life. Bound-water compartments of bone contributed minimally to cyclic fatigue life. These results are complementary with prior Raman studies of monotonic testing of bone that reported decreased toughness and strength with increased collagen disorder and increased stiffness with increased bone mineralization and mineral maturation. This model should be prospectively validated. Raman analysis is a promising tool for the non-destructive evaluation of structural bone allograft quality and may be useful as a screening tool for selection of allograft bone. Acknowledgements. Supported by a grant from the Musculoskeletal Transplant Foundation. The Dudley P. Allen Fellowship (JYD), Wilbert J. Austin Professor of Engineering Chair (CMR) and the Leonard Case Jr. Professor of Engineering Chair (OA) are gratefully acknowledged

Aims. Fixation of osteoporotic proximal humerus fractures remains challenging even with state-of-the-art locking plates. Despite the demonstrated biomechanical benefit of screw tip augmentation with bone cement, the clinical findings have remained unclear, potentially as the optimal augmentation combinations are unknown. The aim of this study was to systematically evaluate the biomechanical benefits of the augmentation options in a humeral locking plate using finite element analysis (FEA). Methods. A total of 64 cement augmentation configurations were analyzed using six screws of a locking plate to virtually fix unstable three-part fractures in 24 low-density proximal humerus models under three physiological loading cases (4,608 simulations). The biomechanical benefit of augmentation was evaluated through an established FEA methodology using the average peri-screw bone strain as a validated predictor of cyclic cut-out failure. Results. The biomechanical benefit was already significant with a single cemented screw and increased with the number of augmented screws, but the configuration was highly influential. The best two-screw (mean 23%, SD 3% reduction) and the worst four-screw (mean 22%, SD 5%) combinations performed similarly. The largest benefits were achieved with augmenting screws purchasing into the calcar and having posteriorly located tips. Local bone mineral density was not directly related to the improvement. Conclusion. The number and configuration of cemented screws strongly determined how augmentation can alleviate the predicted risk of cut-out failure. Screws purchasing in the calcar and posterior humeral head regions may be prioritized. Although requiring clinical corroborations, these findings may explain the controversial results of previous clinical studies not controlling the choices of screw augmentation

Acetabular dysplasia (AD) can cause hip pain and early osteoarthritis. Lateral Centre Edge Angle (LCEA) and sourcil angle (AI) are plain radiographic measures of acetabular morphology, however there is little agreement as to what constitutes mild, moderate or severe dysplasia. This study aims to establish the correlation, if any, between two-dimensional (XR) and three-dimensional (CT) measurements of acetabular morphology and to establish the level of femoral head cover (CTFHC) for different levels of dysplasia. Methods. Governance board approved retrospective study. 353 PAOs performed by the senior author between January 2014 and December 2017 were included. Exclusion criteria were inadequate pre-operative CT imaging and/or plain radiographs, previous pelvic/hip surgery, acetabular retroversion, or femoral head asphericity. Of the remainder, 84 had 3D analysis by clinical graphics giving measurements for CTFHC, LCEA at 1100, 1200, 1300 and sourcil angle (AI). XRLCEA, AI, posterior wall index (PWI), and anterior wall index (AWI), were measured from supine AP pelvis radiographs. Pearson correlation coefficient, and mean CTFHC for stratified LCEAs were calculated. A linear regression model to predict CTFHC from XRLCEA was validated against these. Results. XRLCEA correlated very strongly with total femoral head coverage (Pearson=0.917, p<0.001). Mean CTFHC with XRLCEA between 15°-19.9° was 55% (range 51–59%). At 25° −29.9° mean CTFHC was 61%. There was a linear relation of CTFHC with XR LCEA such that CTFHC = 41.5 + 0.78(XRLCEA). This linear regression model predicted CTFHC 55% (95%CI 54–56%) for XRLCEA of 17.5°, and CTFHC 63% (95%CI 62–64%) for XRLCEA 27.5°. Conclusions. Currently an XRLCEA greater than 25° is considered normal. Previously reported normal values for CTFHC are 71–75%. This study demonstrates that those with acetabular parameters considered normal, may have low CTFHC and AD should be considered as a cause for their hip pain