Aims. The Coronal Plane Alignment of the Knee (CPAK) classification has been developed to predict individual variations in inherent knee alignment. The impact of preoperative and postoperative CPAK classification phenotype on the postoperative clinical outcomes of total knee arthroplasty (TKA) remains elusive. This study aimed to examine the effect of postoperative CPAK classification phenotypes (I to IX), and their pre- to postoperative changes on patient-reported outcome measures (PROMs). Methods. A questionnaire was administered to 340 patients (422 knees) who underwent primary TKA for osteoarthritis (OA) between September 2013 and June 2019. A total of 231 patients (284 knees) responded. The ­Knee Society Score 2011 (KSS 2011), Knee injury and Osteoarthritis Outcome Score-12 (KOOS-12), and Forgotten Joint Score-12 (FJS-12) were used to assess clinical outcomes. Using preoperative and postoperative anteroposterior full-leg radiographs, the arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) were calculated and classified based on the CPAK classification. To investigate the impact on PROMs, multivariable regression analyses using stepwise selection were conducted, considering factors such as age at surgery, time since surgery, BMI, sex, implant use, postoperative aHKA classification, JLO classification, and changes in aHKA and JLO classifications from preoperative to postoperative. Results. The preoperative and postoperative CPAK classifications were predominantly phenotype I (155 knees; 55%) and phenotype V (73 knees; 26%), respectively. The change in the preoperative to postoperative aHKA classification was a significant negative predictive factor for KOOS-12 and FJS-12, while postoperative apex proximal JLO was a significant negative predictive factor for KSS 2011 and KOOS-12. Conclusion. In primary TKA for OA, preoperative and postoperative CPAK phenotypes were associated with PROMs. Alteration in varus/valgus alignment from preoperative to postoperative was recognized as a negative predictive factor for both KOOS-12 and FJS-12. Moreover, the postoperative apex proximal JLO was identified as a negative factor for KSS 2011 and KOOS-12. Determining the target alignment for each preoperative phenotype with reproducibility could improve PROMs. Cite this article: Bone Joint J 2024;106-B(10):1059–1066

Aims. No predictive model has been published to forecast operating time for total knee arthroplasty (TKA). The aims of this study were to design and validate a predictive model to estimate operating time for robotic-assisted TKA based on demographic data, and evaluate the added predictive power of CT scan-based predictors and their impact on the accuracy of the predictive model. Methods. A retrospective study was conducted on 1,061 TKAs performed from January 2016 to December 2019 with an image-based robotic-assisted system. Demographic data included age, sex, height, and weight. The femoral and tibial mechanical axis and the osteophyte volume were calculated from CT scans. These inputs were used to develop a predictive model aimed to predict operating time based on demographic data only, and demographic and 3D patient anatomy data. Results. The key factors for predicting operating time were the surgeon and patient weight, followed by 12 anatomical parameters derived from CT scans. The predictive model based only on demographic data showed that 90% of predictions were within 15 minutes of actual operating time, with 73% within ten minutes. The predictive model including demographic data and CT scans showed that 94% of predictions were within 15 minutes of actual operating time and 88% within ten minutes. Conclusion. The primary factors for predicting robotic-assisted TKA operating time were surgeon, patient weight, and osteophyte volume. This study demonstrates that incorporating 3D patient-specific data can improve operating time predictions models, which may lead to improved operating room planning and efficiency. Cite this article: Bone Jt Open 2022;3(5):383–389

Aims. The aim of this study is to determine the predictors of overall survival (OS) and predictive factors of poor prognosis of conventional high-grade osteosarcoma of the limbs in a single-centre in South Africa. Methods. We performed a retrospective cross-sectional analysis to identify the prognostic factors that predict the OS of patients with histologically confirmed high-grade conventional osteosarcoma of the limbs over ten years. We employed the Cox proportional regression model and the Kaplan-Meier method for statistical analysis. Results. This study comprised 77 patients at a three-year minimum follow-up. The predictors of poor OS were: the median age of ≤ 19 years (hazard ratio (HR) 0.96; 95% confidence interval (CI) 0.92 to 0.99; p = 0.021); median duration of symptoms ≥ five months (HR 0.91; 95% CI 0.83 to 0.99; p < 0.037); metastasis at diagnosis (i.e. Enneking stage III) (HR 3.33; 95% CI 1.81 to 6.00; p < 0.001); increased alkaline phosphatase (HR 3.28; 95% CI 1.33 to 8.11; p < 0.010); palliative treatment (HR 7.27; 95% CI 2.69 to 19.70); p < 0.001); and amputation (HR 3.71; 95% CI 1.12 to 12.25; p < 0.032). In contrast, definitive surgery (HR 0.11; 95% CI 0.03 to 0.38; p < 0.001) and curative treatment (HR 0.18; 95% CI 0.10 to 0.33; p < 0.001) were a protective factor. The Kaplan-Meier median survival time was 24 months, with OS of 57.1% at the three years. The projected five-year event-free survival was 10.3% and OS of 29.8% (HR 0.76; 95% CI 0.52 to 1.12; p = 0.128). Conclusion. In this series of high-grade conventional osteosarcoma of the appendicular skeleton from South Africa, 58.4% (n = 45) had detectable metastases at presentation; hence, an impoverished OS of five years was 29.8%. Large-scale future research is needed to validate our results. Cite this article: Bone Jt Open 2024;5(3):210–217

Aims. Though most humeral shaft fractures heal nonoperatively, up to one-third may lead to nonunion with inferior outcomes. The Radiographic Union Score for HUmeral Fractures (RUSHU) was created to identify high-risk patients for nonunion. Our study evaluated the RUSHU’s prognostic performance at six and 12 weeks in discriminating nonunion within a significantly larger cohort than before. Methods. Our study included 226 nonoperatively treated humeral shaft fractures. We evaluated the interobserver reliability and intraobserver reproducibility of RUSHU scoring using intraclass correlation coefficients (ICCs). Additionally, we determined the optimal cut-off thresholds for predicting nonunion using the receiver operating characteristic (ROC) method. Results. The RUSHU demonstrated good interobserver reliability with an ICC of 0.78 (95% CI 0.72 to 0.83) at six weeks and 0.77 (95% CI 0.71 to 0.82) at 12 weeks. Intraobserver reproducibility was good or excellent for all analyses. Area under the curve in the ROC analysis was 0.83 (95% CI 0.77 to 0.88) at six weeks and 0.89 (95% CI 0.84 to 0.93) at 12 weeks, indicating excellent discrimination. The optimal cut-off values for predicting nonunion were ≤ eight points at six weeks and ≤ nine points at 12 weeks, providing the best specificity-sensitivity trade-off. Conclusion. The RUSHU proves to be a reliable and reproducible radiological scoring system that aids in identifying patients at risk of nonunion at both six and 12 weeks post-injury during non-surgical treatment of humeral shaft fractures. The statistically optimal cut-off values for predicting nonunion are ≤ eight at six weeks and ≤ nine points at 12 weeks post-injury

Aims. A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. Methods. MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS). Results. Predictive performance of the best models per outcome ranged from 0.71 for HOOS-PS to 0.84 for EQ-VAS (HA sample). ML statistically significantly outperformed LR and pre-surgery PROM scores in two out of six cases. Conclusion. MCIDs can be predicted with reasonable performance. ML was able to outperform traditional methods, although only in a minority of cases. Cite this article: Bone Joint Res 2023;12(9):512–521

Aims. The early diagnosis of cauda equina syndrome (CES) is crucial for a favourable outcome. Several studies have reported the use of an ultrasound scan of the bladder as an adjunct to assess the minimum post-void residual volume of urine (mPVR). However, variable mPVR values have been proposed as a threshold without consensus on a value for predicting CES among patients with relevant symptoms and signs. The aim of this study was to perform a meta-analysis and systematic review of the published evidence to identify a threshold mPVR value which would provide the highest diagnostic accuracy in patients in whom the diagnosis of CES is suspected. Methods. The search strategy used electronic databases (PubMed, Medline, EMBASE, and AMED) for publications between January 1996 and November 2021. All studies that reported mPVR in patients in whom the diagnosis of CES was suspected, followed by MRI, were included. Results. A total of 2,115 studies were retrieved from the search. Seven fulfilled the inclusion criteria. These included 1,083 patients, with data available from 734 being available for meta-analysis. In 125 patients, CES was confirmed by MRI. The threshold value of mPVR reported in each study varied and could be categorized into 100 ml, 200 ml, 300 ml, and 500 ml. From the meta-analysis, 200 ml had the highest diagnostic accuracy, with 82% sensitivity (95% confidence interval (CI) 0.72 to 0.90) and 65% specificity (95% CI 0.70 to 0.90). When compared using summative receiver operating characteristic curves, mPVR of 200 ml was superior to other values in predicting the radiological confirmation of CES. Conclusion. mPVR is a useful tool when assessing patients in whom the diagnosis of CES is suspected. Compared with other values a mPVR of 200 ml had superior sensitivity, specificity, and positive and negative predictive values. In a patient with a suggestive history and clinical findings, a mPVR of > 200 ml should further raise the suspicion of CES. Caution is recommended when considering the mPVR in isolation and using it as an ‘exclusion tool’, and it should only be used as an adjunct to a full clinical assessment. Cite this article: Bone Joint J 2023;105-B(5):487–495

Aims. Historically, patients undergoing surgery for adolescent idiopathic scoliosis (AIS) have been nursed postoperatively in a critical care (CC) setting because of the challenges posed by prone positioning, extensive exposures, prolonged operating times, significant blood loss, major intraoperative fluid shifts, cardiopulmonary complications, and difficulty in postoperative pain management. The primary aim of this paper was to determine whether a scoring system, which uses Cobb angle, forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and number of levels to be fused, is a valid method of predicting the need for postoperative critical care in AIS patients who are to undergo scoliosis correction with posterior spinal fusion (PSF). Methods. We retrospectively reviewed all AIS patients who had undergone PSF between January 2018 and January 2020 in a specialist tertiary spinal referral centre. All patients were assessed preoperatively in an anaesthetic clinic. Postoperative care was defined as ward-based (WB) or critical care (CC), based on the preoperative FEV1, FVC, major curve Cobb angle, and the planned number of instrumented levels. Results. Overall, 105 patients were enrolled. Their mean age was 15.5 years (11 to 25) with a mean weight of 55 kg (35 to 103). The mean Cobb angle was 68° (38° to 122°). Of these, 38 patients were preoperatively scored to receive postoperative CC. However, only 19% of the cohort (20/105) actually needed CC-level support. Based on these figures, and an average paediatric intensive care unit stay of one day before stepdown to ward-based care, the potential cost-saving on the first postoperative night for this cohort was over £20,000. There was no statistically significant difference between the Total Pathway Score (TPS), the numerical representation of the four factors being assessed, and the actual level of care received (p = 0.052) or the American Society of Anesthesiologists grade (p = 0.187). Binary logistic regression analysis of the TPS variables showed that the preoperative Cobb angle was the only variable which significantly predicted the need for critical care. Conclusion. Most patients undergoing posterior fusion surgery for AIS do not need critical care. Of the readily available preoperative measures, the Cobb angle is the only predictor of the need for higher levels of care, and has a threshold value of 74.5°. Cite this article: Bone Joint J 2024;106-B(7):713–719

Aims. Radiological residual acetabular dysplasia (RAD) has been reported in up to 30% of children who had successful brace treatment of infant developmental dysplasia of the hip (DDH). Predicting those who will resolve and those who may need corrective surgery is important to optimize follow-up protocols. In this study we have aimed to identify the prevalence and predictors of RAD at two years and five years post-bracing. Methods. This was a single-centre, prospective longitudinal cohort study of infants with DDH managed using a published, standardized Pavlik harness protocol between January 2012 and December 2016. RAD was measured at two years’ mean follow-up using acetabular index-lateral edge (AI-L) and acetabular index-sourcil (AI-S), and at five years using AI-L, AI-S, centre-edge angle (CEA), and acetabular depth ratio (ADR). Each hip was classified based on published normative values for normal, borderline (1 to 2 standard deviations (SDs)), or dysplastic (> 2 SDs) based on sex, age, and laterality. Results. Of 202 infants who completed the protocol, 181 (90%) had two and five years’ follow-up radiographs. At two years, in 304 initially pathological hips, the prevalence of RAD (dysplastic) was 10% and RAD (borderline) was 30%. At five years, RAD (dysplastic) decreased to 1% to 3% and RAD (borderline) decreased to < 1% to 2%. On logistic regression, no variables were predictive of RAD at two years. Only AI-L at two years was predictive of RAD at five years (p < 0.001). If both hips were normal at two years’ follow-up (n = 96), all remained normal at five years. In those with bilateral borderline hips at two years (n = 21), only two were borderline at five years, none were dysplastic. In those with either borderline-dysplastic or bilateral dysplasia at two years (n = 26), three (12%) were dysplastic at five years. Conclusion. The majority of patients with RAD at two years post-brace treatment, spontaneously resolved by five years. Therefore, children with normal radiographs at two years post-brace treatment can be discharged. Targeted follow-up for those with abnormal AI-L at two years will identify the few who may benefit from surgical correction at five years’ follow-up. Cite this article: Bone Joint J 2024;106-B(7):744–750

Aims. Current levels of hip fracture morbidity contribute greatly to the overall burden on health and social care services. Given the anticipated ageing of the population over the coming decade, there is potential for this burden to increase further, although the exact scale of impact has not been identified in contemporary literature. We therefore set out to predict the future incidence of hip fracture and help inform appropriate service provision to maintain an adequate standard of care. Methods. Historical data from the Scottish Hip Fracture Audit (2017 to 2021) were used to identify monthly incidence rates. Established time series forecasting techniques (Exponential Smoothing and Autoregressive Integrated Moving Average) were then used to predict the annual number of hip fractures from 2022 to 2029, including adjustment for predicted changes in national population demographics. Predicted differences in service-level outcomes (length of stay and discharge destination) were analyzed, including the associated financial cost of any changes. Results. Between 2017 and 2021, the number of annual hip fractures increased from 6,675 to 7,797 (15%), with a rise in incidence from 313 to 350 per 100,000 (11%) for the at-risk population. By 2029, a combined average projection forecast the annual number of hip fractures at 10,311, with an incidence rate of 463 per 100,000, representing a 32% increase from 2021. Based upon these projections, assuming discharge rates remain constant, the total overall length of hospital stay following hip fracture in Scotland will increase by 60,699 days per annum, incurring an additional cost of at least £25 million per year. Approximately five more acute hip fracture beds may be required per hospital to accommodate this increased activity. Conclusion. Projection modelling demonstrates that hip fracture burden and incidence will increase substantially by 2029, driven by an ageing population, with substantial implications for health and social care services. Cite this article: Bone Joint J 2024;106-B(1):62–68

The June 2024 Hip & Pelvis Roundup. 360. looks at: Machine learning did not outperform conventional competing risk modelling to predict revision arthroplasty; Unravelling the risks: incidence and reoperation rates for femoral fractures post-total hip arthroplasty; Spinal versus general anaesthesia for hip arthroscopy: a COVID-19 pandemic- and opioid epidemic-driven study; Development and validation of a deep-learning model to predict total hip arthroplasty on radiographs; Ambulatory centres lead in same-day hip and knee arthroplasty success; Exploring the impact of smokeless tobacco on total hip arthroplasty outcomes: a deeper dive into postoperative complications

Aims. Heterotopic ossification (HO) is a common complication after elbow trauma and can cause severe upper limb disability. Although multiple prognostic factors have been reported to be associated with the development of post-traumatic HO, no model has yet been able to combine these predictors more succinctly to convey prognostic information and medical measures to patients. Therefore, this study aimed to identify prognostic factors leading to the formation of HO after surgery for elbow trauma, and to establish and validate a nomogram to predict the probability of HO formation in such particular injuries. Methods. This multicentre case-control study comprised 200 patients with post-traumatic elbow HO and 229 patients who had elbow trauma but without HO formation between July 2019 and December 2020. Features possibly associated with HO formation were obtained. The least absolute shrinkage and selection operator regression model was used to optimize feature selection. Multivariable logistic regression analysis was applied to build the new nomogram: the Shanghai post-Traumatic Elbow Heterotopic Ossification Prediction model (STEHOP). STEHOP was validated by concordance index (C-index) and calibration plot. Internal validation was conducted using bootstrapping validation. Results. Male sex, obesity, open wound, dislocations, late definitive surgical treatment, and lack of use of non-steroidal anti-inflammatory drugs were identified as adverse predictors and incorporated to construct the STEHOP model. It displayed good discrimination with a C-index of 0.80 (95% confidence interval 0.75 to 0.84). A high C-index value of 0.77 could still be reached in the internal validation. The calibration plot showed good agreement between nomogram prediction and observed outcomes. Conclusion. The newly developed STEHOP model is a valid and convenient instrument to predict HO formation after surgery for elbow trauma. It could assist clinicians in counselling patients regarding treatment expectations and therapeutic choices. Cite this article: Bone Joint J 2022;104-B(8):963–971

Aims. The aim of this study was to determine the prevalence and impact of tourniquet use in patients undergoing limb salvage surgery with endoprosthetic reconstruction for a tumour around the knee. Methods. We retrieved data from the Prophylactic Antibiotic Regimens in Tumor Surgery (PARITY) trial; specifically, differences in baseline characteristics, surgical details, and postoperative functional outcomes between patients who had undergone surgery under tourniquet and those who had not. A linear regression model was created to evaluate the impact of tourniquet use on postoperative Toronto Extremity Salvage Scores (TESSs) while controlling for confounding variables. A negative-binomial regression model was constructed to explore predictors of postoperative length of stay (LOS). Results. Of the 604 patients enrolled in the PARITY trial, 421 had tumours around the knee joint, of whom 225 (53%) underwent surgery under tourniquet. The tourniquet group was younger (p = 0.014), more likely to undergo surgery for a tumour of the tibia, and had shorter operating times by a mean of 50 minutes (95% confidence interval 30 to 72; p < 0.001). The adjusted linear regression model found that the use of a tourniquet, a shorter operating time, and a higher baseline TESS independently predicted better function at both three- and six-month follow-up. The negative-binomial regression model showed that tourniquet use, shorter operating time, younger age, and intraoperative tranexamic acid administration independently predicted a shorter LOS in hospital. Conclusion. The results of this study show that in patients undergoing resection of a tumour around the knee and endoprosthetic reconstruction, the use of an intraoperative tourniquet is associated with a shorter operating time, a reduced length of stay in hospital, and a better early functional outcome. Cite this article: Bone Joint J 2022;104-B(10):1168–1173

The August 2023 Shoulder & Elbow Roundup360 looks at: Motor control or strengthening exercises for rotator cuff-related shoulder pain? A multi-arm randomized controlled trial; Does the choice of antibiotic prophylaxis influence reoperation rate in primary shoulder arthroplasty?; Common shoulder injuries in sport: grading the evidence; The use of medial support screw was associated with axillary nerve injury after plate fixation of proximal humeral fracture using a minimally invasive deltoid-splitting approach; MRI predicts outcomes of conservative treatment in patients with lateral epicondylitis; Association between surgeon volume and patient outcomes after elective shoulder arthroplasty; Arthroscopic decompression of calcific tendinitis without cuff repair; Functional outcome after nonoperative management of minimally displaced greater tuberosity fractures and predictors of poorer patient experience

Aims. The aim of this study was to describe the demographic details of patients who sustain a femoral periprosthetic fracture (PPF), the epidemiology of PPFs, PPF characteristics, and the predictors of PPF types in the UK population. Methods. This is a multicentre retrospective cohort study including adult patients presenting to hospital with a new PPF between 1 January 2018 and 31 December 2018. Data collected included: patient characteristics, comorbidities, anticoagulant use, social circumstances, level of mobility, fracture characteristics, Unified Classification System (UCS) type, and details of the original implant. Descriptive analysis by fracture location was performed, and predictors of PPF type were assessed using mixed-effects logistic regression models. Results. In total, 720 femoral PPFs from 27 NHS sites were included. PPF patients were typically elderly (mean 79.9 years (SD 10.6)), female (n = 455; 63.2%), had at least one comorbidity (n = 670; 93.1%), and were reliant on walking aids or bed-/chair-bound prior to admission (n = 419; 61.7%). The study population included 539 (74.9%) hip PPFs, 151 (21.0%) knee PPFs, and 30 (4.2%) dividing type PPFs. For hip (n = 407; 75.5%) and knee (n = 88; 58.3%) arthroplasty UCS B type fractures were most common. Overall, 556 (86.2%) were treated in the presenting hospital and 89 (13.8%) required transfer for treatment. Female sex was the only significant predictor of fracture type (A/B1/C type versus B2/B3) for femoral hip PPFs (odds ratio 0.61 (95% confidence interval 0.41 to 0.91); p = 0.014). Sex, residence type, primary versus revision implant PPF, implant fixation, and time between arthroplasty and PPF were not found to predict fracture type for hip PPFs. Conclusion. This multicentre analysis describes patient and injury factors for patients presenting with femoral PPFs to centres across the UK. These patients are generally elderly and frail, comparable to those sustaining a hip fracture. These data can be useful in planning future services and clinical trials. Cite this article: Bone Joint J 2022;104-B(8):987–996

Aims. The diagnosis of periprosthetic joint infection (PJI) continues to present a significant clinical challenge. New biomarkers have been proposed to support clinical decision-making; among them, synovial fluid alpha-defensin has gained interest. Current research methodology suggests reference methods are needed to establish solid evidence for use of the test. This prospective study aims to evaluate the diagnostic accuracy of high-performance liquid chromatography coupled with the mass spectrometry (LC-MS) method to detect alpha-defensin in synovial fluid. Methods. Between October 2017 and September 2019, we collected synovial fluid samples from patients scheduled to undergo revision surgery for painful total knee arthroplasty (TKA). The International Consensus Meeting criteria were used to classify 33 PJIs and 92 aseptic joints. LC-MS assay was performed to measure alpha-defensin in synovial fluid of all included patients. Sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve (AUC) were calculated to define the test diagnostic accuracy. Results. The AUC was 0.99 (95% confidence interval (CI) 0.98 to 1.00). Receiver operating characteristic (ROC) analysis showed that the optimal cut-off value of synovial fluid alpha-defensin was 1.0 μg/l. The sensitivity of alpha-defensin was 100% (95% CI 96 to 100), the specificity was 97% (95% CI 90 to 98), the positive predictive value was 89.2% (95% CI 82 to 94), and negative predictive value was 100% (95% CI 96 to 100). ROC analysis demonstrated an AUC of 0.99 (95% CI 0.98 to 1.0). Conclusion. The present study confirms the utility of alpha-defensin in the synovial fluid in patients with painful TKA to select cases of PJI. Since LC-MS is still a time-consuming technology and is available in highly specialized laboratories, further translational research studies are needed to take this evidence into routine procedures and promote a new diagnostic approach. Cite this article: Bone Joint J 2022;104-B(9):1047–1051

Aims. Disorders of bone integrity carry a high global disease burden, frequently requiring intervention, but there is a paucity of methods capable of noninvasive real-time assessment. Here we show that miniaturized handheld near-infrared spectroscopy (NIRS) scans, operated via a smartphone, can assess structural human bone properties in under three seconds. Methods. A hand-held NIR spectrometer was used to scan bone samples from 20 patients and predict: bone volume fraction (BV/TV); and trabecular (Tb) and cortical (Ct) thickness (Th), porosity (Po), and spacing (Sp). Results. NIRS scans on both the inner (trabecular) surface or outer (cortical) surface accurately identified variations in bone collagen, water, mineral, and fat content, which then accurately predicted bone volume fraction (BV/TV, inner R. 2. = 0.91, outer R. 2. = 0.83), thickness (Tb.Th, inner R. 2. = 0.9, outer R. 2. = 0.79), and cortical thickness (Ct.Th, inner and outer both R. 2. = 0.90). NIRS scans also had 100% classification accuracy in grading the quartile of bone thickness and quality. Conclusion. We believe this is a fundamental step forward in creating an instrument capable of intraoperative real-time use. Cite this article: Bone Jt Open 2023;4(4):250–261

Aims. Iliopsoas impingement occurs in 4% to 30% of patients after undergoing total hip arthroplasty (THA). Despite a relatively high incidence, there are few attempts at modelling impingement between the iliopsoas and acetabular component, and no attempts at modelling this in a representative cohort of subjects. The purpose of this study was to develop a novel computational model for quantifying the impingement between the iliopsoas and acetabular component and validate its utility in a case-controlled investigation. Methods. This was a retrospective cohort study of patients who underwent THA surgery that included 23 symptomatic patients diagnosed with iliopsoas tendonitis, and 23 patients not diagnosed with iliopsoas tendonitis. All patients received postoperative CT imaging, postoperative standing radiography, and had minimum six months’ follow-up. 3D models of each patient’s prosthetic and bony anatomy were generated, landmarked, and simulated in a novel iliopsoas impingement detection model in supine and standing pelvic positions. Logistic regression models were implemented to determine if the probability of pain could be significantly predicted. Receiver operating characteristic curves were generated to determine the model’s sensitivity, specificity, and area under the curve (AUC). Results. Highly significant differences between the symptomatic and asymptomatic cohorts were observed for iliopsoas impingement. Logistic regression models determined that the impingement values significantly predicted the probability of groin pain. The simulation had a sensitivity of 74%, specificity of 100%, and an AUC of 0.86. Conclusion. We developed a computational model that can quantify iliopsoas impingement and verified its accuracy in a case-controlled investigation. This tool has the potential to be used preoperatively, to guide decisions about optimal cup placement, and postoperatively, to assist in the diagnosis of iliopsoas tendonitis. Cite this article: Bone Jt Open 2023;4(1):3–12

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. 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. Methods. 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. Results. In the derivation cohort, five of the 27 variables were strongly predictive of the CFS (regression coefficient B = 6.383 (95% confidence interval 5.03 to 7.74), p < 0.001): age, Abbreviated Mental Test score, admission haemoglobin concentration (g/l), pre-admission mobility (needs assistance or not), and mechanism of injury (falls from standing height). In the validation cohort, there was strong agreement between the NTFI and the CFS (mean difference 0.02) with no apparent systematic bias. Conclusion. We have developed a clinically applicable tool using easily and routinely measured physiological and functional parameters, which clinicians and researchers can use to guide patient care and to stratify the analysis of quality improvement and research projects. Cite this article: Bone Joint J 2024;106-B(4):412–418

Aims. To investigate the optimal thresholds and diagnostic efficacy of commonly used serological and synovial fluid detection indexes for diagnosing periprosthetic joint infection (PJI) in patients who have rheumatoid arthritis (RA). Methods. The data from 348 patients who had RA or osteoarthritis (OA) and had previously undergone a total knee (TKA) and/or a total hip arthroplasty (THA) (including RA-PJI: 60 cases, RA-non-PJI: 80 cases; OA-PJI: 104 cases, OA-non-PJI: 104 cases) were retrospectively analyzed. A receiver operating characteristic curve was used to determine the optimal thresholds of the CRP, ESR, synovial fluid white blood cell count (WBC), and polymorphonuclear neutrophil percentage (PMN%) for diagnosing RA-PJI and OA-PJI. The diagnostic efficacy was evaluated by comparing the area under the curve (AUC) of each index and applying the results of the combined index diagnostic test. Results. For PJI prediction, the results of serological and synovial fluid indexes were different between the RA-PJI and OA-PJI groups. The optimal cutoff value of CRP for diagnosing RA-PJI was 12.5 mg/l, ESR was 39 mm/hour, synovial fluid WBC was 3,654/μl, and PMN% was 65.9%; and those of OA-PJI were 8.2 mg/l, 31 mm/hour, 2,673/μl, and 62.0%, respectively. In the RA-PJI group, the specificity (94.4%), positive predictive value (97.1%), and AUC (0.916) of synovial fluid WBC were higher than those of the other indexes. The optimal cutoff values of synovial fluid WBC and PMN% for diagnosing RA-PJI after THA were significantly higher than those of TKA. The specificity and positive predictive value of the combined index were 100%. Conclusion. Serum inflammatory and synovial fluid indexes can be used for diagnosing RA-PJI, for which synovial fluid WBC is the best detection index. Combining multiple detection indexes can provide a reference basis for the early and accurate diagnosis of RA-PJI. Cite this article: Bone Joint Res 2023;12(9):559–570