Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles (https://www.ideal-collaboration.net/). Adherence to the framework would provide a robust evidence-based mechanism for developing trust in AI applications, where the underlying algorithms are unlikely to be fully understood by clinical teams.

Cite this article: Bone Joint Res 2024;13(9):507–512.

Aims. The Oxford Shoulder Score (OSS) is a 12-item measure commonly used for the assessment of shoulder surgeries. This study explores whether computerized adaptive testing (CAT) provides a shortened, individually tailored questionnaire while maintaining test accuracy. Methods. A total of 16,238 preoperative OSS were available in the National Joint Registry (NJR) for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey dataset (April 2012 to April 2022). Prior to CAT, the foundational item response theory (IRT) assumptions of unidimensionality, monotonicity, and local independence were established. CAT compared sequential item selection with stopping criteria set at standard error (SE) < 0.32 and SE < 0.45 (equivalent to reliability coefficients of 0.90 and 0.80) to full-length patient-reported outcome measure (PROM) precision. Results. Confirmatory factor analysis (CFA) for unidimensionality exhibited satisfactory fit with root mean square standardized residual (RSMSR) of 0.06 (cut-off ≤ 0.08) but not with comparative fit index (CFI) of 0.85 or Tucker-Lewis index (TLI) of 0.82 (cut-off > 0.90). Monotonicity, measured by H value, yielded 0.482, signifying good monotonic trends. Local independence was generally met, with Yen’s Q3 statistic > 0.2 for most items. The median item count for completing the CAT simulation with a SE of 0.32 was 3 (IQR 3 to 12), while for a SE of 0.45 it was 2 (IQR 2 to 6). This constituted only 25% and 16%, respectively, when compared to the 12-item full-length questionnaire. Conclusion. Calibrating IRT for the OSS has resulted in the development of an efficient and shortened CAT while maintaining accuracy and reliability. Through the reduction of redundant items and implementation of a standardized measurement scale, our study highlights a promising approach to alleviate time burden and potentially enhance compliance with these widely used outcome measures. Cite this article: Bone Joint Res 2024;13(8):392–400

Aims. To map the Oxford Knee Score (OKS) and High Activity Arthroplasty Score (HAAS) items to a common scale, and to investigate the psychometric properties of this new scale for the measurement of knee health. Methods. Patient-reported outcome measure (PROM) data measuring knee health were obtained from the NHS PROMs dataset and Total or Partial Knee Arthroplasty Trial (TOPKAT). Assumptions for common scale modelling were tested. A graded response model (fitted to OKS item responses in the NHS PROMs dataset) was used as an anchor to calibrate paired HAAS items from the TOPKAT dataset. Information curves for the combined OKS-HAAS model were plotted. Bland-Altman analysis was used to compare common scale scores derived from OKS and HAAS items. A conversion table was developed to map between HAAS, OKS, and the common scale. Results. We included 3,329 response sets from 528 patients undergoing knee arthroplasty. These generally met the assumptions of unidimensionality, monotonicity, local independence, and measurement invariance. The HAAS items provided more information than OKS items at high levels of knee health. Combining both instruments resulted in higher test-level information than either instrument alone. The mean error between common scale scores derived from the OKS and HAAS was 0.29 logits. Conclusion. The common scale allowed more precise measurement of knee health than use of either the OKS or HAAS individually. These techniques for mapping PROM instruments may be useful for the standardization of outcome reporting, and pooling results across studies that use either PROM in individual-patient meta-analysis. Cite this article: Bone Joint Res 2023;12(10):624–635

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

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need of human cognition. Owing to the expanding volume of patient information collected, known as ‘big data’, AI is showing promise as a useful tool in healthcare research and across all aspects of patient care pathways. Practical applications in orthopaedic surgery include: diagnostics, such as fracture recognition and tumour detection; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and real-time rehabilitation monitoring and surgical training. However, clinicians should remain cognizant of AI’s limitations, as the development of robust reporting and validation frameworks is of paramount importance to prevent avoidable errors and biases. The aim of this review article is to provide a comprehensive understanding of AI and its subfields, as well as to delineate its existing clinical applications in trauma and orthopaedic surgery. Furthermore, this narrative review expands upon the limitations of AI and future direction. Cite this article: Bone Joint Res 2023;12(7):447–454

Aims

A core outcome set for adult, open lower limb fracture has been established consisting of ‘Walking, gait and mobility’, ‘Being able to return to life roles’, ‘Pain or discomfort’, and ‘Quality of life’. This study aims to identify which outcome measurement instruments (OMIs) should be recommended to measure each core outcome.

Aims

Open lower limb fracture is a life-changing injury affecting 11.5 per 100,000 adults each year, and causes significant morbidity and resource demand on trauma infrastructures. This study aims to identify what, and how, outcomes have been reported for people following open lower limb fracture over ten years.

Aims

The aim of this study was to report the meaningful values of the EuroQol five-dimension three-level questionnaire (EQ-5D-3L) and EuroQol visual analogue scale (EQ-VAS) in patients undergoing primary knee arthroplasty (KA).

Aims. This study investigates the use of the metabolic equivalent of task (MET) score in a young hip arthroplasty population, and its ability to capture additional benefit beyond the ceiling effect of conventional patient-reported outcome measures. Methods. From our electronic database of 751 hip arthroplasty procedures, 221 patients were included. Patients were excluded if they had revision surgery, an alternative hip procedure, or incomplete data either preoperatively or at one-year follow-up. Included patients had a mean age of 59.4 years (SD 11.3) and 54.3% were male, incorporating 117 primary total hip and 104 hip resurfacing arthroplasty operations. Oxford Hip Score (OHS), EuroQol five-dimension questionnaire (EQ-5D), and the MET were recorded preoperatively and at one-year follow-up. The distribution was examined reporting the presence of ceiling and floor effects. Validity was assessed correlating the MET with the other scores using Spearman’s rank correlation coefficient and determining responsiveness. A subgroup of 93 patients scoring 48/48 on the OHS were analyzed by age, sex, BMI, and preoperative MET using the other metrics to determine if differences could be established despite scoring identically on the OHS. Results. Postoperatively the OHS and EQ-5D demonstrate considerable negatively skewed distributions with ceiling effects of 41.6% and 53.8%, respectively. The MET was normally distributed postoperatively with no relevant ceiling effect. Weak-to-moderate significant correlations were found between the MET and the other two metrics. In the 48/48 subgroup, no differences were found comparing groups with the EQ-5D, however significantly higher mean MET scores were demonstrated for patients aged < 60 years (12.7 (SD 4.7) vs 10.6 (SD 2.4), p = 0.008), male patients (12.5 (SD 4.5) vs 10.8 (SD 2.8), p = 0.024), and those with preoperative MET scores > 6 (12.6 (SD 4.2) vs 11.0 (SD 3.3), p = 0.040). Conclusion. The MET is normally distributed in patients following hip arthroplasty, recording levels of activity which are undetectable using the OHS. Cite this article: Bone Joint Res 2022;11(5):317–326

Aims

Bi-unicondylar arthroplasty (Bi-UKA) is a bone and anterior cruciate ligament (ACL)-preserving alternative to total knee arthroplasty (TKA) when the patellofemoral joint is preserved. The aim of this study is to investigate the clinical outcomes and biomechanics of Bi-UKA.

Outcomes following different types of surgical intervention for femoroacetabular impingement (FAI) are well reported individually but comparative data are deficient. The purpose of this study was to conduct a systematic review (SR) and meta-analysis to analyze the outcomes following surgical management of FAI by hip arthroscopy (HA), anterior mini open approach (AMO), and surgical hip dislocation (SHD). This SR was registered with PROSPERO. An electronic database search of PubMed, Medline, and EMBASE for English and German language articles over the last 20 years was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We specifically analyzed and compared changes in patient-reported outcome measures (PROMs), α-angle, rate of complications, rate of revision, and conversion to total hip arthroplasty (THA). A total of 48 articles were included for final analysis with a total of 4,384 hips in 4,094 patients. All subgroups showed a significant correction in mean α angle postoperatively with a mean change of 28.8° (95% confidence interval (CI) 21 to 36.5; p < 0.01) after AMO, 21.1° (95% CI 15.1 to 27; p < 0.01) after SHD, and 20.5° (95% CI 16.1 to 24.8; p < 0.01) after HA. The AMO group showed a significantly higher increase in PROMs (3.7; 95% CI 3.2 to 4.2; p < 0.01) versus arthroscopy (2.5; 95% CI 2.3 to 2.8; p < 0.01) and SHD (2.4; 95% CI 1.5 to 3.3; p < 0.01). However, the rate of complications following AMO was significantly higher than HA and SHD. All three surgical approaches offered significant improvements in PROMs and radiological correction of cam deformities. All three groups showed similar rates of revision procedures but SHD had the highest rate of conversion to a THA. Revision rates were similar for all three revision procedures

Aims

We aimed to evaluate the long-term impact of fracture-related infection (FRI) on patients’ physical health and psychological wellbeing. For this purpose, quality of life after successful surgical treatment of FRIs of long bones was assessed.

Patient-reported outcome measures (PROMs) are being used increasingly in total knee arthroplasty (TKA). We conducted a systematic review aimed at identifying psychometrically sound PROMs by appraising their measurement properties. Studies concerning the development and/or evaluation of the measurement properties of PROMs used in a TKA population were systematically retrieved via PubMed, Web of Science, Embase, and Scopus. Ratings for methodological quality and measurement properties were conducted according to updated COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology. Of the 155 articles on 34 instruments included, nine PROMs met the minimum requirements for psychometric validation and can be recommended to use as measures of TKA outcome: Oxford Knee Score (OKS); OKS–Activity and Participation Questionnaire (OKS-APQ); 12-item short form Knee Injury and Osteoarthritis Outcome (KOOS-12); KOOS Physical function Short form (KOOS-PS); Western Ontario and McMaster Universities Arthritis Index-Total Knee Replacement function short form (WOMAC-TKR); Lower Extremity Functional Scale (LEFS); Forgotten Joint Score (FJS); Patient’s Knee Implant Performance (PKIP); and University of California Los Angeles (UCLA) activity score. The pain and function subscales in WOMAC, as well as the pain, function, and quality of life subscales in KOOS, were validated psychometrically as standalone subscales instead of as whole instruments. However, none of the included PROMs have been validated for all measurement properties. Thus, further studies are still warranted to evaluate those PROMs. Use of the other 25 scales and subscales should be tempered until further studies validate their measurement properties. Cite this article: Bone Joint Res 2021;10(3):203–217

Aims

To evaluate if union of clavicle fractures can be predicted at six weeks post-injury by the presence of bridging callus on ultrasound.

Aims

The primary aim of this study was to compare the hip-specific functional outcome of robotic assisted total hip arthroplasty (rTHA) with manual total hip arthroplasty (mTHA) in patients with osteoarthritis (OA). Secondary aims were to compare general health improvement, patient satisfaction, and radiological component position and restoration of leg length between rTHA and mTHA.

Aims

To analyze the potential role of synovial fluid peptidase activity as a measure of disease burden and predictive biomarker of progression in knee osteoarthritis (KOA).

Aims

The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA).

Aims

The primary aim of the study was to compare the knee-specific functional outcome of robotic unicompartmental knee arthroplasty (rUKA) with manual total knee arthroplasty (mTKA) for the management of isolated medial compartment osteoarthritis. Secondary aims were to compare length of hospital stay, general health improvement, and satisfaction between rUKA and mTKA.

Objectives

Our primary aim was to describe migration of the Exeter stem with a 32 mm head on highly crosslinked polyethylene and whether this is influenced by age. Our secondary aims were to assess functional outcome, satisfaction, activity, and bone mineral density (BMD) according to age.