Aims. Navigation devices are designed to improve a surgeon’s accuracy in positioning the acetabular and femoral components in total hip arthroplasty (THA). The purpose of this study was to both evaluate the accuracy of an optical computer-assisted surgery (CAS)
Custom triflange acetabular components (CTACs) play an important role in reconstructive orthopaedic surgery, particularly in revision total hip arthroplasty (rTHA) and pelvic tumour resection procedures. Accurate CTAC positioning is essential to successful surgical outcomes. While prior studies have explored CTAC positioning in rTHA, research focusing on tumour cases and implant flange positioning precision remains limited. Additionally, the impact of intraoperative navigation on positioning accuracy warrants further investigation. This study assesses CTAC positioning accuracy in tumour resection and rTHA cases, focusing on the differences between preoperative planning and postoperative implant positions. A multicentre observational cohort study in Australia between February 2017 and March 2021 included consecutive patients undergoing acetabular reconstruction with CTACs in rTHA (Paprosky 3A/3B defects) or tumour resection (including Enneking P2 peri-acetabular area). Of 103 eligible patients (104 hips), 34 patients (35 hips) were analyzed.Aims
Methods
Robotic-assisted total knee arthroplasty (TKA) has proven higher accuracy, fewer alignment outliers, and improved short-term clinical outcomes when compared to conventional TKA. However, evidence of cost-effectiveness and individual superiority of one system over another is the subject of further research. Despite its growing adoption rate, published results are still limited and comparative studies are scarce. This review compares characteristics and performance of five currently available systems, focusing on the information and feedback each system provides to the surgeon, what the systems allow the surgeon to modify during the operation, and how each system then aids execution of the surgical plan. Cite this article: Abstract
Post-traumatic periprosthetic acetabular fractures are rare but serious. Few studies carried out on small cohorts have reported them in the literature. The aim of this work is to describe the specific characteristics of post-traumatic periprosthetic acetabular fractures, and the outcome of their surgical treatment in terms of function and complications. Patients with this type of fracture were identified retrospectively over a period of six years (January 2016 to December 2021). The following data were collected: demographic characteristics, date of insertion of the prosthesis, details of the intervention, date of the trauma, characteristics of the fracture, and type of treatment. Functional results were assessed with the Harris Hip Score (HHS). Data concerning complications of treatment were collected.Aims
Methods
Nearly 99,000 total knee arthroplasties (TKAs) are performed in UK annually. Despite plenty of research, the satisfaction rate of this surgery is around 80%. One of the important intraoperative factors affecting the outcome is alignment. The relationship between joint obliquity and functional outcomes is not well understood. Therefore, a study is required to investigate and compare the effects of two types of alignment (mechanical and kinematic) on functional outcomes and range of motion. The aim of the study is to compare navigated kinematically aligned TKAs (KA TKAs) with navigated mechanically aligned TKA (MA TKA) in terms of function and ROM. We aim to recruit a total of 96 patients in the trial. The patients will be recruited from clinics of various consultants working in the trust after screening them for eligibility criteria and obtaining their informed consent to participate in this study. Randomization will be done prior to surgery by a software. The primary outcome measure will be the Knee injury and Osteoarthritis Outcome Score The secondary outcome measures include Oxford Knee Score, ROM, EuroQol five-dimension questionnaire, EuroQol visual analogue scale, 12-Item Short-Form Health Survey (SF-12), and Forgotten Joint Score. The scores will be calculated preoperatively and then at six weeks, six months, and one year after surgery. The scores will undergo a statistical analysis.Aims
Methods
Limb alignment in total knee arthroplasty (TKA) influences periarticular soft-tissue tension, biomechanics through knee flexion, and implant survival. Despite this, there is no uniform consensus on the optimal alignment technique for TKA. Neutral mechanical alignment facilitates knee flexion and symmetrical component wear but forces the limb into an unnatural position that alters native knee kinematics through the arc of knee flexion. Kinematic alignment aims to restore native limb alignment, but the safe ranges with this technique remain uncertain and the effects of this alignment technique on component survivorship remain unknown. Anatomical alignment aims to restore predisease limb alignment and knee geometry, but existing studies using this technique are based on cadaveric specimens or clinical trials with limited follow-up times. Functional alignment aims to restore the native plane and obliquity of the joint by manipulating implant positioning while limiting soft tissue releases, but the results of high-quality studies with long-term outcomes are still awaited. The drawbacks of existing studies on alignment include the use of surgical techniques with limited accuracy and reproducibility of achieving the planned alignment, poor correlation of intraoperative data to long-term functional outcomes and implant survivorship, and a paucity of studies on the safe ranges of limb alignment. Further studies on alignment in TKA should use surgical adjuncts (e.g. robotic technology) to help execute the planned alignment with improved accuracy, include intraoperative assessments of knee biomechanics and periarticular soft-tissue tension, and correlate alignment to long-term functional outcomes and survivorship.
The use of technology to assess balance and alignment during total knee surgery can provide an overload of numerical data to the surgeon. Meanwhile, this quantification holds the potential to clarify and guide the surgeon through the surgical decision process when selecting the appropriate bone recut or soft tissue adjustment when balancing a total knee. Therefore, this paper evaluates the potential of deploying supervised machine learning (ML) models to select a surgical correction based on patient-specific intra-operative assessments. Based on a clinical series of 479 primary total knees and 1,305 associated surgical decisions, various ML models were developed. These models identified the indicated surgical decision based on available, intra-operative alignment, and tibiofemoral load data.Aims
Methods
