Aims. The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance. Methods. A group of 697 patients underwent a first-time revision of a total hip (THA) or total knee arthroplasty (TKA) at our institution between 2012 and 2018. Preoperative anteroposterior (AP) and lateral radiographs, and historical and comorbidity information were collected from their electronic records. Each patient was defined as having loose or fixed components based on the operation notes. We trained a series of convolutional neural network (CNN) models to predict a diagnosis of loosening at the time of surgery from the preoperative radiographs. We then added historical data about the patients to the best performing model to create a final model and tested it on an independent dataset. Results. The convolutional neural network we built performed well when detecting loosening from radiographs alone. The first model built de novo with only the radiological image as input had an accuracy of 70%. The final model, which was built by fine-tuning a publicly available model named DenseNet, combining the AP and lateral radiographs, and incorporating information from the patient’s history, had an accuracy, sensitivity, and specificity of 88.3%, 70.2%, and 95.6% on the independent test dataset. It performed better for cases of revision THA with an accuracy of 90.1%, than for cases of revision TKA with an accuracy of 85.8%. Conclusion. This study showed that machine learning can detect prosthetic loosening from radiographs. Its accuracy is enhanced when using highly trained public algorithms, and when adding clinical data to the algorithm. While this algorithm may not be sufficient in its present state of development as a standalone metric of loosening, it is currently a useful augment for clinical decision making. Cite this article: Bone Joint J 2020;102-B(6 Supple A):101–106

Aims. The Oswestry-Bristol Classification (OBC) is an MRI-specific assessment tool to grade trochlear dysplasia. The aim of this study is to validate clinically the OBC by demonstrating its use in selecting treatments that are safe and effective. Methods. The OBC and the patellotrochlear index were used as part of the Oswestry Patellotrochlear Algorithm (OPTA) to guide the surgical treatment of patients with patellar instability. Patients were assigned to one of four treatment groups: medial patellofemoral ligament reconstruction (MPFLr); MPFLr + tibial tubercle distalization (TTD); trochleoplasty; or trochleoplasty + TTD. A prospective analysis of a longitudinal patellofemoral database was performed. Between 2012 and 2018, 202 patients (233 knees) with a mean age of 24.2 years (SD 8.1), with recurrent patellar instability were treated by two fellowship-trained consultant sports/knee surgeons at The Robert Jones and Agnes Hunt Orthopaedic Hospital. Clinical efficacy of each treatment group was assessed by Kujala, International Knee Documentation Committee (IKDC), and EuroQol five-dimension questionnaire (EQ-5D) scores at baseline, and up to 60 months postoperatively. Their safety was assessed by complication rate and requirement for further surgery. The pattern of clinical outcome over time was analyzed using mixed regression modelling. Results. In all, 135 knees (mean age 24.9 years (SD 9.4)) were treated using a MPFLr. Ten knees (7.4%) required additional surgery. A total of 50 knees (mean age 24.4 years (SD 6.3)) were treated using MPFLr + TTD. Ten (20%) required additional surgery. A total of 20 knees (mean age 19.5 years (SD 3.0)) were treated using trochleoplasty + TTD. Three patients (15%) required additional surgery. In each treatment group, there was a significant improvement in Kujala, IKDC, and EQ-5D at one year postoperatively (p < 0.001) with a recognized level of overall complication rate. Conclusion. The OBC is a valid assessment tool to grade patients with trochlear dysplasia and, when used as part of the OPTA, helps to determine treatments that are safe and effective. This fulfils the requirements for its application in mainstream clinical practice. Cite this article: Bone Joint J 2021;103-B(10):1586–1594

Aims. Obtaining solid implant fixation is crucial in revision total knee arthroplasty (rTKA) to avoid aseptic loosening, a major reason for re-revision. This study aims to validate a novel grading system that quantifies implant fixation across three anatomical zones (epiphysis, metaphysis, diaphysis). Methods. Based on pre-, intra-, and postoperative assessments, the novel grading system allocates a quantitative score (0, 0.5, or 1 point) for the quality of fixation achieved in each anatomical zone. The criteria used by the algorithm to assign the score include the bone quality, the size of the bone defect, and the type of fixation used. A consecutive cohort of 245 patients undergoing rTKA from 2012 to 2018 were evaluated using the current novel scoring system and followed prospectively. In addition, 100 first-time revision cases were assessed radiologically from the original cohort and graded by three observers to evaluate the intra- and inter-rater reliability of the novel radiological grading system. Results. At a mean follow-up of 90 months (64 to 130), only two out of 245 cases failed due to aseptic loosening. Intraoperative grading yielded mean scores of 1.87 (95% confidence interval (CI) 1.82 to 1.92) for the femur and 1.96 (95% CI 1.92 to 2.0) for the tibia. Only 3.7% of femoral and 1.7% of tibial reconstructions fell below the 1.5-point threshold, which included the two cases of aseptic loosening. Interobserver reliability for postoperative radiological grading was 0.97 for the femur and 0.85 for the tibia. Conclusion. A minimum score of 1.5 points for each skeletal segment appears to be a reasonable cut-off to define sufficient fixation in rTKA. There were no revisions for aseptic loosening at mid-term follow-up when this fixation threshold was achieved or exceeded. When assessing first-time revisions, this novel grading system has shown excellent intra- and interobserver reliability. Cite this article: Bone Joint J 2024;106-B(5):468–474

Aims. This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA). Methods. Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay. Results. The predictability of the ANN model, area under the curve (AUC) = 0.801, was similar to the logistic regression model (AUC = 0.796) and identified certain variables as important factors to predict same-day discharge. The ten most important factors favouring same-day discharge in the ANN model include preoperative sodium, preoperative international normalized ratio, BMI, age, anaesthesia type, operating time, dyspnoea status, functional status, race, anaemia status, and chronic obstructive pulmonary disease (COPD). Six of these variables were also found to be significant on logistic regression analysis. Conclusion. Both ANN modelling and logistic regression analysis revealed clinically important factors in predicting patients who can undergo safely undergo same-day discharge from an outpatient TKA. The ANN model provides a beneficial approach to help determine which perioperative factors can predict same-day discharge as of 2018 perioperative recovery protocols. Cite this article: Bone Joint J 2021;103-B(8):1358–1366

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Fungal periprosthetic joint infections (PJIs) are rare, but their diagnosis and treatment are highly challenging. The purpose of this study was to investigate the clinical outcomes of patients with fungal PJIs treated with two-stage exchange knee arthroplasty combined with prolonged antifungal therapy.

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The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population.

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The aim of this study was to compare a bicruciate-retaining (BCR) total knee arthroplasty (TKA) with a posterior cruciate-retaining (CR) TKA design in terms of kinematics, measured using fluoroscopy and stability as micromotion using radiostereometric analysis (RSA).

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In cases of severe periprosthetic joint infection (PJI) of the knee, salvage procedures such as knee arthrodesis (KA) or above-knee amputation (AKA) must be considered. As both treatments result in limitations in quality of life (QoL), we aimed to compare outcomes and factors influencing complication rates, mortality, and mobility.

This study demonstrates a significant correlation between the American Knee Society (AKS) Clinical Rating System and the Oxford Knee Score (OKS) and provides a validated prediction tool to estimate score conversion. A total of 1022 patients were prospectively clinically assessed five years after TKR and completed AKS assessments and an OKS questionnaire. Multivariate regression analysis demonstrated significant correlations between OKS and the AKS knee and function scores but a stronger correlation (r = 0.68, p < 0.001) when using the sum of the AKS knee and function scores. Addition of body mass index and age (other statistically significant predictors of OKS) to the algorithm did not significantly increase the predictive value. The simple regression model was used to predict the OKS in a group of 236 patients who were clinically assessed nine to ten years after TKR using the AKS system. The predicted OKS was compared with actual OKS in the second group. Intra-class correlation demonstrated excellent reliability (r = 0.81, 95% confidence intervals 0.75 to 0.85) for the combined knee and function score when used to predict OKS. Our findings will facilitate comparison of outcome data from studies and registries using either the OKS or the AKS scores and may also be of value for those undertaking meta-analyses and systematic reviews. Cite this article: Bone Joint J 2015;97-B:503–9

Osteochondritis Dissecans (OCD) is a condition for which the aetiology remains unknown. It affects subchondral bone and secondarily its overlying cartilage and is mostly found in the knee. It can occur in adults, but is generally identified when growth remains, when it is referred to as juvenile OCD. As the condition progresses, the affected subchondral bone separates from adjacent healthy bone, and can lead to demarcation and separation of its associated articular cartilage. Any symptoms which arise relate to the stage of the disease. Early disease without separation of the lesion results in pain. Separation of the lesion leads to mechanical symptoms and swelling and, in advanced cases, the formation of loose bodies. Early identification of OCD is essential as untreated OCD can lead to the premature degeneration of the joint, whereas appropriate treatment can halt the disease process and lead to healing. Establishing the stability of the lesion is a key part of providing the correct treatment. Stable lesions, particularly in juvenile patients, have greater propensity to heal with non-surgical treatment, whereas unstable or displaced lesions usually require surgical management. This article discusses the aetiology, clinical presentation and prognosis of OCD in the knee. It presents an algorithm for treatment, which aims to promote healing of native hyaline cartilage and to ensure joint congruity. Take home message: Although there is no clear consensus as to the best treatment of OCD, every attempt should be made to retain the osteochondral fragment when possible as, with a careful surgical technique, there is potential for healing even in chronic lesions. Cite this article: Bone Joint J 2016;98-B:723–9

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Access to total knee arthroplasty (TKA) is sometimes restricted for patients with severe obesity (BMI ≥ 40 kg/m²). This study compares the cost per quality-adjusted life year (QALY) associated with TKA in patients with a BMI above and below 40 kg/m² to examine whether this is supported.

We retrospectively reviewed the records of 1150 computer-assisted total knee replacements and analysed the clinical and radiological outcomes of 45 knees that had arthritis with a pre-operative recurvatum deformity. The mean pre-operative hyperextension deformity of 11° (6° to 15°), as measured by navigation at the start of the operation, improved to a mean flexion deformity of 3.1° (0° to 7°) post-operatively. A total of 41 knees (91%) were managed using inserts ≤ 12.5 mm thick, and none had mediolateral laxity > 2 mm from a mechanical axis of 0° at the end of the surgery. At a mean follow-up of 26.4 months (13 to 48) there was significant improvement in the mean Knee Society, Oxford knee and Western Ontario and McMaster Universities Osteoarthritis Index scores compared with the pre-operative values. The mean knee flexion improved from 105° (80° to 125°) pre-operatively to 131° (120° to 145°), and none of the limbs had recurrent recurvatum. These early results show that total knee replacement using computer navigation and an algorithmic approach for arthritic knees with a recurvatum deformity can give excellent radiological and functional outcomes without recurrent deformity

Instability is a common indication for early revision after both primary and revision total knee arthroplasty (TKA), accounting for up to 20% in the literature. The number of TKAs performed annually continues to climb exponentially, thus having an effective algorithm for treatment is essential. This relies on a thorough pre- and intra-operative assessment of the patient. The underlying cause of the instability must be identified initially and subsequently, the surgeon must be able to balance the flexion and extension gaps and be comfortable using a variety of constrained implants. This review describes the assessment of the unstable TKA, and the authors’ preferred form of treatment for these difficult cases where the source of instability is often multifactorial. Cite this article: Bone Joint J 2016;98-B(1 Suppl A):116–19

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The objective of this study is to assess the use of ultrasound (US) as a radiation-free imaging modality to reconstruct 3D anatomy of the knee for use in preoperative templating in knee arthroplasty.

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The aim of this study is to compare the effectiveness and safety of thromboprophylactic treatments in patients undergoing primary total knee arthroplasty (TKA).

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A comprehensive classification for coronal lower limb alignment with predictive capabilities for knee balance would be beneficial in total knee arthroplasty (TKA). This paper describes the Coronal Plane Alignment of the Knee (CPAK) classification and examines its utility in preoperative soft tissue balance prediction, comparing kinematic alignment (KA) to mechanical alignment (MA).

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The optimal management of an infrapopliteal deep venous thrombosis (IDVT) following total knee arthroplasty (TKA) remains unknown. The risk of DVT propagation and symptom progression must be balanced against potential haemorrhagic complications associated with administration of anticoagulation therapy. The current study reports on a cohort of patients diagnosed with IDVT following TKA who were treated with aspirin, followed closely for development of symptoms, and scanned with ultrasound to determine resolution of IDVT.

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Surgeons commonly resect additional distal femur during primary total knee arthroplasty (TKA) to correct a flexion contracture, which leads to femoral joint line elevation. There is a paucity of data describing the effect of joint line elevation on mid-flexion stability and knee kinematics. Thus, the goal of this study was to quantify the effect of joint line elevation on mid-flexion laxity.

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It has been shown that the preoperative modification of risk factors associated with obesity may reduce complications after total knee arthroplasty (TKA). However, the optimal method of doing so remains unclear. The aim of this study was to investigate whether a preoperative Risk Stratification Tool (RST) devised in our institution could reduce unexpected intensive care unit (ICU) transfers and 90-day emergency department (ED) visits, readmissions, and reoperations after TKA in obese patients.

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Modern total knee arthroplasty (TKA) prostheses are designed to restore near normal kinematics including high flexion. Kneeling is a high flexion, kinematically demanding activity after TKA. The debate about design choice has not yet been informed by six-degrees-of-freedom in vivo kinematics. This prospective randomized clinical trial compared kneeling kinematics in three TKA designs.