Aims. The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for
The COVID-19 pandemic has caused unprecedented disruption to elective orthopaedic services. The primary objective of this study was to examine changes in functional scores in patients awaiting total hip arthroplasty (THA), total knee arthroplasty (TKA), and unicompartmental knee arthroplasty (UKA). Secondary objectives were to investigate differences between these groups and identify those in a health state ‘worse than death’ (WTD). In this prospective cohort study, preoperative Oxford hip and knee scores (OHS/OKS) were recorded for patients added to a waiting list for THA, TKA, or UKA, during the initial eight months of the COVID-19 pandemic, and repeated at 14 months into the pandemic (mean interval nine months (SD 2.84)). EuroQoL five-dimension five-level health questionnaire (EQ-5D-5L) index scores were also calculated at this point in time, with a negative score representing a state WTD. OHS/OKS were analyzed over time and in relation to the EQ-5D-5L.Aims
Methods
To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models.Aims
Methods
Functional alignment (FA) in total knee arthroplasty (TKA) aims to achieve balanced gaps by adjusting implant positioning while minimizing changes to constitutional joint line obliquity (JLO). Although FA uses kinematic alignment (KA) as a starting point, the final implant positions can vary significantly between these two approaches. This study used the Coronal Plane Alignment of the Knee (CPAK) classification to compare differences between KA and final FA positions. A retrospective analysis compared pre-resection and post-implantation alignments in 2,116 robotic-assisted FA TKAs. The lateral distal femoral angle (LDFA) and medial proximal tibial angle (MPTA) were measured to determine the arithmetic hip-knee-ankle angle (aHKA = MPTA – LDFA), JLO (JLO = MPTA + LDFA), and CPAK type. The primary outcome was the proportion of knees that varied ≤ 2° for aHKA and ≤ 3° for JLO from their KA to FA positions, and direction and magnitude of those changes per CPAK phenotype. Secondary outcomes included proportion of knees that maintained their CPAK phenotype, and differences between sexes.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
This study aimed to identify the effect of anatomical tibial component (ATC) design on load distribution in the periprosthetic tibial bone of Koreans using finite element analysis (FEA). 3D finite element models of 30 tibiae in Korean women were created. A symmetric tibial component (STC, NexGen LPS-Flex) and an ATC (Persona) were used in surgical simulation. We compared the FEA measurements (von Mises stress and principal strains) around the stem tip and in the medial half of the proximal tibial bone, as well as the distance from the distal stem tip to the shortest anteromedial cortical bone. Correlations between this distance and FEA measurements were then analyzed.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.
Little biomechanical information is available about kinematically aligned (KA) total knee arthroplasty (TKA). The purpose of this study was to simulate the kinematics and kinetics after KA TKA and mechanically aligned (MA) TKA with four different limb alignments. Bone models were constructed from one volunteer (normal) and three patients with three different knee deformities (slight, moderate and severe varus). A dynamic musculoskeletal modelling system was used to analyse the kinematics and the tibiofemoral contact force. The contact stress on the tibial insert, and the stress to the resection surface and medial tibial cortex were examined by using finite element analysis.Objectives
Materials and Methods
There is a large amount of evidence available
about the relative merits of unicompartmental and total knee arthroplasty
(UKA and TKA). Based on the same evidence, different people draw
different conclusions and as a result, there is great variability
in the usage of UKA. The revision rate of UKA is much higher than TKA and so some
surgeons conclude that UKA should not be performed. Other surgeons
believe that the main reason for the high revision rate is that
UKA is easy to revise and, therefore, the threshold for revision
is low. They also believe that UKA has many advantages over TKA
such as a faster recovery, lower morbidity and mortality and better
function. They therefore conclude that UKA should be undertaken
whenever appropriate. The solution to this argument is to minimise the revision rate
of UKA, thereby addressing the main disadvantage of UKA. The evidence
suggests that this will be achieved if surgeons use UKA for at least
20% of their knee arthroplasties and use implants that are appropriate
for these broad indications. Cite this article:
