Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
To determine the major risk factors for unplanned reoperations (UROs) following corrective surgery for adult spinal deformity (ASD) and their interactions, using machine learning-based prediction algorithms and game theory. Patients who underwent surgery for ASD, with a minimum of two-year follow-up, were retrospectively reviewed. In total, 210 patients were included and randomly allocated into training (70% of the sample size) and test (the remaining 30%) sets to develop the machine learning algorithm. Risk factors were included in the analysis, along with clinical characteristics and parameters acquired through diagnostic radiology.Aims
Methods
The primary aim of this study is to assess the survival of the uncemented hydroxyapatite (HA) coated Trident II acetabular component as part of a hybrid total hip arthroplasty (THA) using a cemented Exeter stem. The secondary aims are to assess the complications, joint-specific function, health-related quality of life, and radiological signs of loosening of the acetabular component. A single-centre, prospective cohort study of 125 implants will be undertaken. Patients undergoing hybrid THA at the study centre will be recruited. Inclusion criteria are patients suitable for the use of the uncemented acetabular component, aged 18 to 75 years, willing and able to comply with the study protocol, and provide informed consent. Exclusion criteria includes patients not meeting study inclusion criteria, inadequate bone stock to support fixation of the prosthesis, a BMI > 40 kg/m2, or THA performed for pain relief in those with severely restricted mobility.Aims
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The June 2024 Oncology Roundup360 looks at: Chondrosarcoma of the femur: is local recurrence influenced by the presence of an extraosseous component?; Diagnostic challenges in low-grade central osteosarcoma; Single osteotomy technique for frozen autograft (pedicled freezing) in patients with malignant bone tumours; Unplanned resection for small superficial soft-tissue sarcomas: disastrous or simply bad?; Inactivation and replantation of the knee joint: an infeasible surgical method; Active surveillance of diffuse-type tenosynovial giant cell tumours: a retrospective, multicentre cohort study.
Economic evaluation provides a framework for assessing the costs and consequences of alternative programmes or interventions. One common vehicle for economic evaluations in the healthcare context is the decision-analytic model, which synthesizes information on parameter inputs (for example, probabilities or costs of clinical events or health states) from multiple sources and requires application of mathematical techniques, usually within a software program. A plethora of decision-analytic modelling-based economic evaluations of orthopaedic interventions have been published in recent years. This annotation outlines a number of issues that can help readers, reviewers, and decision-makers interpret evidence from decision-analytic modelling-based economic evaluations of orthopaedic interventions. Cite this article:
Patient dissatisfaction following primary total knee arthroplasty (TKA) with manual jig-based instruments has been reported to be as high as 30%. Robotic-assisted total knee arthroplasty (RA-TKA) has been increasingly used in an effort to improve patient outcomes, however there is a paucity of literature examining patient satisfaction after RA-TKA. This study aims to identify the incidence of patients who were not satisfied following RA-TKA and to determine factors associated with higher levels of dissatisfaction. This was a retrospective review of 674 patients who underwent primary TKA between October 2016 and September 2020 with a minimum two-year follow-up. A five-point Likert satisfaction score was used to place patients into two groups: Group A were those who were very dissatisfied, dissatisfied, or neutral (Likert score 1 to 3) and Group B were those who were satisfied or very satisfied (Likert score 4 to 5). Patient demographic data, as well as preoperative and postoperative patient-reported outcome measures, were compared between groups.Aims
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Aims. Patient-specific glenoid guides (PSGs) claim an improvement in
accuracy and reproducibility of the positioning of components in
total shoulder arthroplasty (TSA). The results have not yet been
confirmed in a prospective clinical trial. Our aim was to assess
whether the use of PSGs in patients with osteoarthritis of the shoulder
would allow accurate and reliable implantation of the glenoid component. Patients and Methods. A total of 17 patients (three men and 14 women) with a mean age
of 71 years (53 to 81) awaiting TSA were enrolled in the study.
Pre- and post-operative version and inclination of the glenoid were
measured on CT scans, using 3D
The impact of a diaphyseal femoral deformity on knee alignment varies according to its severity and localization. The aims of this study were to determine a method of assessing the impact of diaphyseal femoral deformities on knee alignment for the varus knee, and to evaluate the reliability and the reproducibility of this method in a large cohort of osteoarthritic patients. All patients who underwent a knee arthroplasty from 2019 to 2021 were included. Exclusion criteria were genu valgus, flexion contracture (> 5°), previous femoral osteotomy or fracture, total hip arthroplasty, and femoral rotational disorder. A total of 205 patients met the inclusion criteria. The mean age was 62.2 years (SD 8.4). The mean BMI was 33.1 kg/m2 (SD 5.5). The radiological measurements were performed twice by two independent reviewers, and included hip knee ankle (HKA) angle, mechanical medial distal femoral angle (mMDFA), anatomical medial distal femoral angle (aMDFA), femoral neck shaft angle (NSA), femoral bowing angle (FBow), the distance between the knee centre and the top of the FBow (DK), and the angle representing the FBow impact on the knee (C’KS angle).Aims
Methods
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. We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct patient-specific musculoskeletal models of the pre-diseased knee. Subsequently, implantations were simulated using the MA method, and a previously developed optimization technique was employed to find the optimal implant position that minimized the root mean square deviation between pre-diseased and postoperative ligament strains and kinematics.Aims
Methods
Olecranon fractures are usually caused by falling directly on to the olecranon or following a fall on to an outstretched arm. Displaced fractures of the olecranon with a stable ulnohumeral joint are commonly managed by open reduction and internal fixation. The current predominant method of management of simple displaced fractures with ulnohumeral stability (Mayo grade IIA) in the UK and internationally is a low-cost technique using tension band wiring. Suture or suture anchor techniques have been described with the aim of reducing the hardware related complications and reoperation. An all-suture technique has been developed to fix the fracture using strong synthetic sutures alone. The aim of this trial is to investigate the clinical and cost-effectiveness of tension suture repair versus traditional tension band wiring for the surgical fixation of Mayo grade IIA fractures of the olecranon. SOFFT is a multicentre, pragmatic, two-arm parallel-group, non-inferiority, randomized controlled trial. Participants will be assigned 1:1 to receive either tension suture fixation or tension band wiring. 280 adult participants will be recruited. The primary outcome will be the Disabilities of the Arm, Shoulder and Hand (DASH) score at four months post-randomization. Secondary outcome measures include DASH (at 12, 18, and 24 months), pain, Net Promotor Score (patient satisfaction), EuroQol five-dimension five-level score (EQ-5D-5L), radiological union, complications, elbow range of motion, and re-operations related to the injury or to remove metalwork. An economic evaluation will assess the cost-effectiveness of treatments.Aims
Methods
To investigate the extent of bone development around the scaffold of custom triflange acetabular components (CTACs) over time. We performed a single-centre historical prospective cohort study, including all patients with revision THA using the aMace CTAC between January 2017 and March 2021. A total of 18 patients (18 CTACs) were included. Models of the hemipelvis and the scaffold component of the CTACs were created by segmentation of CT scans. The CT scans were performed immediately postoperatively and at least one year after surgery. The amount of bone in contact with the scaffold was analyzed at both times, and the difference was calculated.Aims
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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). 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.Aims
Methods
The rate of day-case total knee arthroplasty (TKA) in the UK is currently approximately 0.5%. Reducing length of stay allows orthopaedic providers to improve efficiency, increase operative throughput, and tackle the rising demand for joint arthroplasty surgery and the COVID-19-related backlog. Here, we report safe delivery of day-case TKA in an NHS trust via inpatient wards with no additional resources. Day-case TKAs, defined as patients discharged on the same calendar day as surgery, were retrospectively reviewed with a minimum follow-up of six months. Analysis of hospital and primary care records was performed to determine readmission and reattendance rates. Telephone interviews were conducted to determine patient satisfaction.Aims
Methods
The aim of this study was to determine the rate of indocyanine green (ICG) staining of bone and soft-tissue tumours, as well as the stability and accuracy of ICG fluorescence imaging in detecting tumour residuals during surgery for bone and soft-tissue tumours. ICG fluorescence imaging was performed during surgery in 34 patients with bone and soft-tissue tumours. ICG was administered intravenously at a dose of 2 mg/kg over a period of 60 minutes on the day prior to surgery. The tumour stain rate and signal-to-background ratio of each tumour were post hoc analyzed. After tumour resection, the tumour bed was scanned to locate sites with fluorescence residuals, which were subsequently inspected and biopsied.Aims
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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. 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).Aims
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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:
To investigate if preoperative CT improves detection of unstable trochanteric hip fractures. A single-centre prospective study was conducted. Patients aged 65 years or older with trochanteric hip fractures admitted to Stavanger University Hospital (Stavanger, Norway) were consecutively included from September 2020 to January 2022. Radiographs and CT images of the fractures were obtained, and surgeons made individual assessments of the fractures based on these. The assessment was conducted according to a systematic protocol including three classification systems (AO/Orthopaedic Trauma Association (OTA), Evans Jensen (EVJ), and Nakano) and questions addressing specific fracture patterns. An expert group provided a gold-standard assessment based on the CT images. Sensitivities and specificities of surgeons’ assessments were estimated and compared in regression models with correlations for the same patients. Intra- and inter-rater reliability were presented as Cohen’s kappa and Gwet’s agreement coefficient (AC1).Aims
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This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images. The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a calibration phantom were automatically segmented using previously trained deep-learning models. The Hounsfield units of each voxel were converted into density (mg/cm3). Then, a deep-learning model trained by manual landmark selection of 315 cases was developed to select the landmarks at the proximal femur to rotate the CT volume to the neutral position. Finally, the CT volume of the femur was projected onto the coronal plane, and the areal BMD of the proximal femur (CT-aBMD) was quantified. CT-aBMD correlated to DXA-BMD, and a receiver operating characteristic (ROC) analysis quantified the accuracy in diagnosing osteoporosis.Aims
Methods