Around the world, the emergence of robotic technology has improved surgical precision and accuracy in total knee arthroplasty (TKA). This territory-wide study compares the results of various robotic TKA (R-TKA) systems with those of conventional TKA (C-TKA) and computer-navigated TKA (N-TKA). This is a retrospective study utilizing territory-wide data from the Clinical Data Analysis and Reporting System (CDARS). All patients who underwent primary TKA in all 47 public hospitals in Hong Kong between January 2021 and December 2023 were analyzed. Primary outcomes were the percentage use of various robotic and navigation platforms. Secondary outcomes were: 1) mean length of stay (LOS); 2) 30-day emergency department (ED) attendance rate; 3) 90-day ED attendance rate; 4) 90-day reoperation rate; 5) 90-day mortality rate; and 6) surgical time.Aims
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The aims of this study were to develop an automatic system capable of calculating four radiological measurements used in the diagnosis and monitoring of cerebral palsy (CP)-related hip disease, and to demonstrate that these measurements are sufficiently accurate to be used in clinical practice. We developed a machine-learning system to automatically measure Reimer’s migration percentage (RMP), acetabular index (ACI), head shaft angle (HSA), and neck shaft angle (NSA). The system automatically locates points around the femoral head and acetabulum on pelvic radiographs, and uses these to calculate measurements. The system was evaluated on 1,650 pelvic radiographs of children with CP (682 females and 968 males, mean age 8.3 years (SD 4.5)). Each radiograph was manually measured by five clinical experts. Agreement between the manual clinical measurements and the automatic system was assessed by mean absolute deviation (MAD) from the mean manual measurement, type 1 and type 2 intraclass correlation coefficients (ICCs), and a linear mixed-effects model (LMM) for assessing bias.Aims
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Aim. Fast and accurate identification of pathogens causing periprosthetic joint infections (PJI) is essential to initiate effective antimicrobial treatment. Culture-based approaches frequently yield false negative results, despite clear signs of infection. This may be due to the use of general growth media, which do not mimic the conditions at site of infection. Possible alternative approaches include DNA-based techniques, the use of in vivo-like media and isothermal microcalorimetry (ITC). We developed a synthetic synovial fluid (SSF) medium that closely resembles the in vivo microenvironment and allows to grow and study PJI pathogens in physiologically relevant conditions. In this study we investigated whether the use of ITC in combination with the SSF medium can improve accuracy and time to detection in the context of PJI. Methods. In this study, 120 synovial fluid samples were included, aspirated from patients with clinical signs of PJI. For these samples microbiology data (obtained in the clinical microbiology lab using standard procedures) and next generation sequencing (NGS) data, were available. The samples were incubated in the SSF medium at different oxygen levels (21% O. 2. , 3% O. 2. and 0% O. 2. ) for 10 days. Every 24h, the presence of growth was checked. From positive samples, cultures were purified on Columbia blood agar and identified using MALDI-TOF. In parallel, heat produced by metabolically active microorganisms present in the samples was measured using ITC (calScreener, Symcel), (96h at 37°C, in SSF, BHI and thioglycolate). From the resulting thermograms the ‘time to activity’ could be derived. The accuracy and time to detection were compared between the different detection methods. Results. So far, seven samples were investigated. Using conventional culture-based techniques only 14.3% of the samples resulted in positive cultures, whereas NGS indicated the presence of microorganisms in 57.1% of the samples (with 3/7 samples being polymicrobial). Strikingly, 100% of the samples resulted in positive cultures after incubation in the SSF medium, with time to detection varying from 1 to 9 days. MALDI-TOF revealed all samples to be polymicrobial after cultivation in SSF, identifying organisms not detected by conventional techniques or NGS. For the samples investigated so far, signals obtained with ITC were low, probably reflecting the low microbial load in the first set of samples. Conclusion. These initial results highlight the potential of the SSF medium as an alternative culture medium to detect microorganisms in PJI context. Further studies with additional samples are ongoing; in addition, the microcalorimetry
Aim. Diagnosis of prosthetic joint infection are often complicated by the presence of biofilm, which hampers bacteria dislodging from the implants, thus affecting sensitivity of cultures. In the last 20 years several studies have evidenced the usefulness of implant sonication to improve microbial recovery from biofilm formed on inert substrates. More recently, treatment of prosthetic joints and tissues with Dithiothreitol, a sulphur compound already used in routine diagnostic
Aim. Periprosthetic joint infection (PJI) is one of the most serious and frequent complications in prosthetic surgery. Despite significant improvements in the criteria for diagnosis of PJI, the diagnostic
Background. The molecular mechanisms underlying non-union bone fractures largely remain elusive. Recently, spatial transcriptomics approaches for musculoskeletal tissue samples have been developed requiring direct placement of histology sections on barcoded slides. However, Formalin-Fixed-Paraffin-Embedded (FFPE) bone sections have been associated with limited RNA quality and read depth compared to soft tissue. Here, we test spatial transcriptomics
Introduction. The surgical treatment of critical-sized bone defects with complex three-dimensional (3D) geometries is a challenge for the treating surgeon. Additive manufacturing such as 3D printing enables the production of highly individualized bone implants meeting the shape of the patient's bone defect and including a tunable internal structure. In this study, we showcase the design process for patient-specific implants with critical-sized tibia defects. Methods. Two clinical cases of patients with critical tibia defects (size 63×20×21 mm and 50×24×17 mm) were chosen. Brainlab software was used for segmentation of CT data generating 3D models of the defects. The implant construction involves multiple stages. Initially, the outer shell is precisely defined. Subsequently, the specified volume is populated with internal structures using Voronoi, Gyroid, and NaCl crystal structures. Variation in pore size (1.6 mm and 1.0 mm) was accomplished by adjusting scaffold size and material thickness. Results. An algorithmic design process in Rhino and Grasshopper was successfully applied to generate model implants for the tibia from Ct data. By integrating a precise mesh into an outer shell, a scaffold with controlled porosity was designed. In terms of the internal design, both Voronoi and Gyroid form macroscopically homogeneous properties, while NaCl, exhibits irregularities in density and consequently, in the strength of the structure. Data implied that Voronoi and Gyroid structures adapt more precisely to complex and irregular outer shapes of the implants. Conclusion. In proof-of-principle studies customized tibia implants were successfully generated and printed as model implants based on resin. Further studies will include more patient data sets to refine the
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
The October 2024 Shoulder & Elbow Roundup360 looks at: Proximal humeral fractures with vascular compromise; Outcomes and challenges of revision arthroscopic rotator cuff repair: a systematic review; Evaluating treatment effectiveness for lateral elbow tendinopathy: a systematic review and network meta-analysis; Tendon transfer techniques for irreparable subscapularis tears: a comparative review; Impact of subscapularis repair in reverse shoulder arthroplasty; Isolated subscapularis tears strongly linked to shoulder pseudoparesis; Nexel and Coonrad-Morrey total elbow arthroplasties show comparable revision rates in New Zealand study; 3D MRI matches 3D CT in assessing bone loss and shoulder morphology in dislocation cases.
The subject of noise in the operating theatre was recognized as early as 1972 and has been compared to noise levels on a busy highway. While noise-induced hearing loss in orthopaedic surgery specifically has been recognized as early as the 1990s, it remains poorly studied. As a result, there has been renewed focus in this occupational hazard. Noise level is typically measured in decibels (dB), whereas noise adjusted for human perception uses A-weighted sound levels and is expressed in dBA. Mean operating theatre noise levels range between 51 and 75 dBA, with peak levels between 80 and 119 dBA. The greatest sources of noise emanate from powered surgical instruments, which can exceed levels as high as 140 dBA. Newer technology, such as robotic-assisted systems, contribute a potential new source of noise. This article is a narrative review of the deleterious effects of prolonged noise exposure, including noise-induced hearing loss in the operating theatre team and the patient, intraoperative miscommunication, and increased cognitive load and stress, all of which impact the surgical team’s overall performance. Interventions to mitigate the effects of noise exposure include the use of quieter surgical equipment, the implementation of sound-absorbing personal protective equipment, or changes in communication protocols. Future research endeavours should use advanced research methods and embrace technological innovations to proactively mitigate the effects of operating theatre noise. Cite this article:
Aims. To report the development of the technique for minimally invasive lumbar decompression using robotic-assisted navigation. Methods. Robotic planning software was used to map out bone removal for a laminar decompression after registration of CT scan images of one cadaveric specimen. A specialized acorn-shaped bone removal robotic drill was used to complete a robotic lumbar laminectomy. Post-procedure advanced imaging was obtained to compare actual bony decompression to the surgical plan. After confirming accuracy of the technique, a minimally invasive robotic-assisted laminectomy was performed on one 72-year-old female patient with lumbar spinal stenosis. Postoperative advanced imaging was obtained to confirm the decompression. Results. A
To explore key stakeholder views around feasibility and acceptability of trials seeking to prevent post-traumatic osteoarthritis (PTOA) following knee injury, and provide guidance for next steps in PTOA trial design. Healthcare professionals, clinicians, and/or researchers (HCP/Rs) were surveyed, and the data were presented at a congress workshop. A second and related survey was then developed for people with joint damage caused by knee injury and/or osteoarthritis (PJDs), who were approached by a UK Charity newsletter or Oxford involvement registry. Anonymized data were collected and analyzed in Qualtrics.Aims
Methods
Advanced 3D imaging and CT-based navigation have emerged as valuable tools to use in total knee arthroplasty (TKA), for both preoperative planning and the intraoperative execution of different philosophies of alignment. Preoperative planning using CT-based 3D imaging enables more accurate prediction of the size of components, enhancing surgical
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. 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.Aims
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The June 2024 Wrist & Hand Roundup360 looks at: One-year outcomes of the anatomical front and back reconstruction for scapholunate dissociation; Limited intercarpal fusion versus proximal row carpectomy in the treatment of SLAC or SNAC wrist: results after 3.5 years; Prognostic factors for clinical outcomes after arthroscopic treatment of traumatic central tears of the triangular fibrocartilage complex; The rate of nonunion in the MRI-detected occult scaphoid fracture: a multicentre cohort study; Does correction of carpal malalignment influence the union rate of scaphoid nonunion surgery?; Provision of a home-based video-assisted therapy programme in thumb carpometacarpal arthroplasty; Is replantation associated with better hand function after traumatic hand amputation than after revision amputation?; Diagnostic performance of artificial intelligence for detection of scaphoid and distal radius fractures: a systematic review.
The aim of mechanical alignment in total knee arthroplasty is to align all knees into a fixed neutral position, even though not all knees are the same. As a result, mechanical alignment often alters a patient’s constitutional alignment and joint line obliquity, resulting in soft-tissue imbalance. This annotation provides an overview of how the Coronal Plane Alignment of the Knee (CPAK) classification can be used to predict imbalance with mechanical alignment, and then offers practical guidance for bone balancing, minimizing the need for soft-tissue releases. Cite this article:
Introduction. Recent technological advancements have led to the introduction of robotic-assisted total knee arthroplasty to improve the accuracy and precision of bony resections and implant position. However, the in vivo accuracy is not widely reported. The primary objective of this study is to determine the accuracy and precision of a cut block positioning robotic arm. Method. Seventy-seven patients underwent total knee arthroplasty with various
The aim of this study was to determine the fracture haematoma (fxH) proteome after multiple trauma using label-free proteomics, comparing two different fracture treatment strategies. A porcine multiple trauma model was used in which two fracture treatment strategies were compared: early total care (ETC) and damage control orthopaedics (DCO). fxH was harvested and analyzed using liquid chromatography-tandem mass spectrometry. Per group, discriminating proteins were identified and protein interaction analyses were performed to further elucidate key biomolecular pathways in the early fracture healing phase.Aims
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OpenPredictor, a machine learning-enabled clinical decision aid, has been developed to manage backlogs in elective surgeries. It aims to optimise the use of high volume, low complexity surgical pathways by accurately stratifying patient risk, thereby facilitating the allocation of patients to the most suitable surgical sites. The tool augments elective surgical pathways by providing automated secondary opinions for perioperative risk assessments, enhancing decision-making. Its primary application is in elective sites utilising lighter pre-assessment methods, identifying patients with minimal complication risks and those high-risk individuals who may benefit from early pre-assessment. The Phase 1 clinical evaluation of OpenPredictor entailed a prospective analysis of 156 patient records from elective hip and knee joint replacement surgeries. Using a polynomial logistic regression model, patients were categorised into high, moderate, and low-risk groups. This categorisation incorporated data from various sources, including patient demographics, co-morbidities, blood tests, and overall health status. In identifying patients at risk of postoperative complications, OpenPredictor demonstrated parity with consultant-led preoperative assessments. It accurately flagged 70% of patients who later experienced complications as moderate or high risk. The tool's efficiency in risk prediction was evidenced by its balanced accuracy (75.6%), sensitivity (70% with a 95% confidence interval of 62.05% to 76.91%), and a high negative predictive value (96.7%). OpenPredictor presents a scalable and consistent solution for managing elective surgery pathways, comparable in performance to secondary consultant opinions. Its integration into pre-assessment