Understanding spinopelvic mechanics is important for the success of total hip arthroplasty (THA). Despite significant advancements in appreciating spinopelvic balance, numerous challenges remain. It is crucial to recognize the individual variability and postoperative changes in spinopelvic parameters and their consequential impact on prosthetic component positioning to mitigate the risk of dislocation and enhance postoperative outcomes. This review describes the integration of advanced diagnostic approaches, enhanced technology, implant considerations, and surgical planning, all tailored to the unique anatomy and biomechanics of each patient. It underscores the importance of accurately predicting postoperative spinopelvic mechanics, selecting suitable imaging techniques, establishing a consistent nomenclature for spinopelvic stiffness, and considering implant-specific strategies. Furthermore, it highlights the potential of artificial intelligence to personalize care. Cite this article:
Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures.Aims
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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. 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
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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:
This study aimed to quantify the shoulder kinematics during an apprehension-relocation test in patients with anterior shoulder instability (ASI) and glenoid bone loss using the radiostereometric analysis (RSA) method. Kinematics were compared with the patient’s contralateral healthy shoulder. A total of 20 patients with ASI and > 10% glenoid bone loss and a healthy contralateral shoulder were included. RSA imaging of the patient’s shoulders was performed during a repeated apprehension-relocation test. Bone volume models were generated from CT scans, marked with anatomical coordinate systems, and aligned with the digitally reconstructed bone projections on the RSA images. The glenohumeral joint (GHJ) kinematics were evaluated in the anteroposterior and superoinferior direction of: the humeral head centre location relative to the glenoid centre; and the humeral head contact point location on the glenoid.Aims
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The primary objective of this study was to develop a validated classification system for assessing iatrogenic bone trauma and soft-tissue injury during total hip arthroplasty (THA). The secondary objective was to compare macroscopic bone trauma and soft-tissues injury in conventional THA (CO THA) versus robotic arm-assisted THA (RO THA) using this classification system. This study included 30 CO THAs versus 30 RO THAs performed by a single surgeon. Intraoperative photographs of the osseous acetabulum and periacetabular soft-tissues were obtained prior to implantation of the acetabular component, which were used to develop the proposed classification system. Interobserver and intraobserver variabilities of the proposed classification system were assessed.Aims
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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 workflow and optimizing the
Aims. Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA. Methods. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied. Eligible studies of THA patients that conducted at least one type of objective functional assessment both pre- and postoperatively were identified through Embase, Medline/PubMed, and Cochrane Central database-searching from inception to 15 September 2023. The assessments included were subgrouped for analysis: gait analysis, motion analysis, wearables, and strength tests. Results. A total of 130 studies using 15 distinct objective functional assessment methods (FAMs) were identified. The most frequently used method was instrumented gait/motion analysis, followed by the Timed-Up-and-Go test (TUG), 6 minute walk test, timed stair climbing test, and various strength tests. These assessments were characterized by their diagnostic
The aim of this study was to compare the migration of the femoral component, five years postoperatively, between patients with a highly cross-linked polyethylene (HXLPE) insert and those with a conventional polyethylene (PE) insert in an uncemented Triathlon fixed insert cruciate-retaining total knee arthroplasty (TKA). Secondary aims included clinical outcomes and patient-reported outcome measures (PROMs). We have previously reported the migration and outcome of the tibial components in these patients. A double-blinded randomized controlled trial was conducted including 96 TKAs. The migration of the femoral component was measured with radiostereometry (RSA) at three and six months and one, two, and five years postoperatively. PROMs were collected preoperatively and at all periods of follow-up.Aims
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To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project protocol. This included use of de-identified Scottish regional clinical data of patients referred for consideration of THA/TKA, held in a secure data environment designed for artificial intelligence (AI) inference. Only preoperative radiology reports were included. NLP algorithms were based on the freely available GatorTron model, a LLM trained on over 82 billion words of de-identified clinical text. Two inference tasks were performed: assessment after model-fine tuning (50 Epochs and three cycles of k-fold cross validation), and external validation.Aims
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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:
The aim was to assess whether robotic-assisted total knee arthroplasty (rTKA) had greater knee-specific outcomes, improved fulfilment of expectations, health-related quality of life (HRQoL), and patient satisfaction when compared with manual TKA (mTKA). A randomized controlled trial was undertaken (May 2019 to December 2021), and patients were allocated to either mTKA or rTKA. A total of 100 patients were randomized, 50 to each group, of whom 43 rTKA and 38 mTKA patients were available for review at 12 months following surgery. There were no statistically significant preoperative differences between the groups. The minimal clinically important difference in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score was defined as 7.5 points.Aims
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Ganz’s studies made it possible to address joint deformities on both the femoral and acetabular side brought about by Perthes’ disease. Femoral head reduction osteotomy (FHRO) was developed to improve joint congruency, along with periacetabular osteotomy (PAO), which may enhance coverage and containment. The purpose of this study is to show the clinical and morphological outcomes of the technique and the use of an implemented planning approach. From September 2015 to December 2021, 13 FHROs were performed on 11 patients for Perthes’ disease in two centres. Of these, 11 hips had an associated PAO. A specific CT- and MRI-based protocol for virtual simulation of the corrections was developed. Outcomes were assessed with radiological parameters (sphericity index, extrusion index, integrity of the Shenton’s line, lateral centre-edge angle (LCEA), Tönnis angle), and clinical parameters (range of motion, visual analogue scale (VAS) for pain, Merle d'Aubigné-Postel score, modified Harris Hip Score (mHHS), and EuroQol five-dimension five-level health questionnaire (EQ-5D-5L)). Early and late complications were reported.Aims
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Refobacin Bone Cement R and Palacos Overall, 75 patients were included in the study and 71 were available at two years postoperatively. Prior to surgery, they were randomized to one of the three combinations studied: Palacos cement with use of the Optivac mixing system, Refobacin with use of the Optivac system, and Refobacin with use of the Optipac system. Cemented MS30 stems and cemented Exceed acetabular components were used in all hips. Postoperative radiographs were used to assess the quality of the cement mantle according to Barrack et al, and the position and migration of the femoral stem. Harris Hip Score, Oxford Hip Score, Forgotten Joint Score, and University of California, Los Angeles Activity Scale were collected.Aims
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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. 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.Aims
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Periacetabular osteotomy (PAO) is widely recognized as a demanding surgical procedure for acetabular reorientation. Reports about the learning curve have primarily focused on complication rates during the initial learning phase. Therefore, our aim was to assess the PAO learning curve from an analytical perspective by determining the number of PAOs required for the duration of surgery to plateau and the accuracy to improve. The study included 118 consecutive PAOs in 106 patients. Of these, 28 were male (23.7%) and 90 were female (76.3%). The primary endpoint was surgical time. Secondary outcome measures included radiological parameters. Cumulative summation analysis was used to determine changes in surgical duration. A multivariate linear regression model was used to identify independent factors influencing surgical time.Aims
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Achieving accurate implant positioning and restoring native hip biomechanics are key surgeon-controlled technical objectives in total hip arthroplasty (THA). The primary objective of this study was to compare the reproducibility of the planned preoperative centre of hip rotation (COR) in patients undergoing robotic arm-assisted THA versus conventional THA. This prospective randomized controlled trial (RCT) included 60 patients with symptomatic hip osteoarthritis undergoing conventional THA (CO THA) versus robotic arm-assisted THA (RO THA). Patients in both arms underwent pre- and postoperative CT scans, and a patient-specific plan was created using the robotic software. The COR, combined offset, acetabular orientation, and leg length discrepancy were measured on the pre- and postoperative CT scanogram at six weeks following surgery.Aims
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Postoperative length of stay (LOS) and discharge dispositions following arthroplasty can be used as surrogate measurements for improvements in patients’ pathways and costs. With the increasing use of robotic technology in arthroplasty, it is important to assess its impact on LOS. The aim of this study was to identify factors associated with decreased LOS following robotic arm-assisted total hip arthroplasty (RO THA) compared with the conventional technique (CO THA). This large-scale, single-institution study included 1,607 patients of any age who underwent 1,732 primary THAs for any indication between May 2019 and January 2023. The data which were collected included the demographics of the patients, LOS, type of anaesthetic, the need for treatment in a post-anaesthesia care unit (PACU), readmission within 30 days, and discharge disposition. Univariate and multivariate logistic regression models were used to identify factors and the characteristics of patients which were associated with delayed discharge.Aims
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