Methods

The James Lind Alliance (JLA) methodology for Priority Setting Partnerships was followed. An initial survey invited patients and healthcare professionals from the UK to submit any uncertainties regarding soft-tissue knee injury prevention, diagnosis, treatment, and rehabilitation and delivery of care. Over 1,000 questions were received. From these, 74 questions (identifying common concerns) were formulated and checked against the best available evidence. An interim survey was then conducted and 27 questions were taken forward to the final workshop, held in January 2023, where they were discussed, ranked, and scored in multiple rounds of prioritization. This was conducted by healthcare professionals, patients, and carers.

Methods

The James Lind Alliance methodology was followed; a modified nominal group technique was used in the final workshop. An initial survey invited patients and healthcare professionals to submit their uncertainties regarding soft tissue knee injury prevention, diagnosis, treatment, rehabilitation, and delivery of care. Seventy-four questions were formulated to encompass common concerns. These were checked against best available evidence. Following the interim survey, 27 questions were taken forward to the final workshop in January 2023, where they were discussed, ranked, and scored in multiple rounds of prioritisation by groups of healthcare professionals, patients, and carers.

Objectives

Biomechanics is an essential form of measurement in the understanding of the development and progression of osteoarthritis (OA). However, the number of participants in biomechanical studies are often small and there is limited ways to share or combine data from across institutions or studies. This is essential for applying modern machine learning methods, where large, complex datasets can be used to identify patterns in the data. Using these data-driven approaches, it could be possible to better predict the optimal interventions for patients at an early stage, potentially avoiding pain and inappropriate surgery or rehabilitation. In this project we developed a prototype database platform for combining and sharing biomechanics datasets. The database includes methods for importing and standardising data and associated variables, to create a seamless, searchable combined dataset of both healthy and knee OA biomechanics.

Methods

Data was curated through calls to members of the OATech Network+ (https://www.oatechnetwork.org/). The requirements were 3D motion capture data from previous studies that related to analysing the biomechanics of knee OA, including participants with OA at any stage of progression plus healthy controls. As a minimum we required kinematic data of the lower limbs, plus associated kinetic data (i.e. ground reaction forces). Any additional, complementary data such as EMG could also be provided. Relevant ethical approvals had to be in place that allowed re-use of the data for other research purposes. The datasets were uploaded to a University hosted cloud platform. The database platform was developed using Javascript and hosted on a Windows server, located and managed within the department.

Introduction

Component mal-positioning in total hip replacement (THR) and total knee replacement (TKR) can increase the risk of revision for various reasons. Compared to conventional surgery, relatively improved accuracy of implant positioning can be achieved using computer assisted technologies including navigation, patient-specific jigs, and robotic systems. However, it is not known whether application of these technologies has improved prosthesis survival in the real-world. This study aimed to compare risk of revision for all-causes following primary THR and TKR, and revision for dislocation following primary THR performed using computer assisted technologies compared to conventional technique.

Methods

We performed an observational study using National Joint Registry data. All adult patients undergoing primary THR and TKR for osteoarthritis between 01/04/2003 to 31/12/2020 were eligible. Patients who received metal-on-metal bearing THR were excluded. We generated propensity score weights, using Sturmer weight trimming, based on: age, gender, ASA grade, side, operation funding, year of surgery, approach, and fixation. Specific additional variables included position and bearing for THR and patellar resurfacing for TKR. For THR, effective sample sizes and duration of follow up for conventional versus computer-guided and robotic-assisted analyses were 9,379 and 10,600 procedures, and approximately 18 and 4 years, respectively. For TKR, effective sample sizes and durations of follow up for conventional versus computer-guided, patient-specific jigs, and robotic-assisted groups were 92,579 procedures over 18 years, 11,665 procedures over 8 years, and 644 procedures over 3 years, respectively. Outcomes were assessed using Kaplan-Meier analysis and expressed using hazard ratios (HR) and 95% confidence intervals (CI).

Background

Osteochondral allograft (OCA) transplantation is a clinically and cost-effective option for symptomatic cartilage defects. In 2017 we initiated a program for OCA transplantation for complex chondral and osteochondral defects as a UK tertiary referral centre.

Aim

To characterise the complications, re-operation rate, graft survivorship and clinical outcomes of knee OCA transplantation.

Background

Meniscal tears affect 222 per 100,000 of the population and can be managed non-operatively or operatively with an arthroscopic partial meniscectomy (APM), meniscal repair or meniscal transplantation. The purpose of this review is to summarise the outcomes following treatment with a meniscal tear and explore correlations between outcomes.

Methodology

A systematic review was performed of MEDLINE, EMBASE, AMED and the Cochrane Central Register of Controlled Trials to identify prospective studies describing the outcomes of patients with a meniscal tear. Comparisons were made of outcomes between APM and non-operative groups. Outcomes were graphically presented over time for all treatment interventions. Pearson's correlations were calculated between outcome timepoints.

Introduction

Recent research has questioned the role of arthroscopic meniscectomy in patients with a meniscal tear leading to the development of treatment recommendations for these patients. There is a clear need to understand patient perceptions of living with a meniscal tear in order to plan future research and treatment guidelines.

Aims

To explore the experiences and expectations of treatment of young patients with a meniscal tear of the knee

Background

The Forgotten Joint Score (FJS) is a 12-item patient reported outcome measurement instrument. It was developed with classical test theory, without testing assumptions such as unidimensionality (all items reflect one underlying factor), appropriate weighting of each item, no differential item function (DIF, different groups answer the same way), and monotonicity (people with higher function have higher score). We applied item response theory (IRT) to improve the validity of FJS to contemporary standards to optimise it for ongoing use.

Research Questions

Does the FJS reflect one latent trait? Can an IRT model be fitted to the FJS to provide interval-scaled measurement?

Introduction

Previous research has demonstrated no clinically significant benefit of arthroscopic meniscectomy in patients with a meniscal tear, however, patients included in these studies would not meet current treatment recommendations. Prior to further randomised controlled trials (RCTs) research is needed to understand a younger population in more detail.

Aim

To describe the baseline characteristics of patients with a meniscal tear and explore any association between baseline characteristics and outcome.

Introduction

The knee is the most commonly injured joint in sporting accidents. They cause substantial disability, time off work and long-term problems. There remains a limited number of high-quality randomised controlled trials assessing first time, acute soft tissue knee injuries. Key areas requiring answers include prevention, diagnosis, treatment, rehabilitation and delivery of care. In association with the James Lind Alliance, this BASK, BOSTAA and BOA supported prioritising exercise was undertaken over a year.

Methodology

The James Lind Alliance methodology was followed. An initial survey invited patients and healthcare professionals to submit their uncertainties regarding soft tissue knee injury prevention, diagnosis, treatment, rehabilitation and delivery of care. Over 1000 questions were submitted. Seventy-four questions were formulated to encompass common concerns. These were checked against best available evidence. Following the interim survey, 27 questions were taken forward to the final workshop in January 2023, where they were discussed, ranked and scored in multiple rounds of prioritisation by groups of healthcare professionals, patients and carers.

Introduction

The paediatric population present unique challenges to the knee surgeon, particularly when treating recurrent patellofemoral instability(PFI), the management of which is poorly standardised. Through the EPPIC BASK National Trainee Collaborative, we aimed to identify which procedures (and in which combination) are being used to surgically manage recurrent PFI in skeletally immature patients across the UK.

Methods

A retrospective national service evaluation via a trainee collaborative analysing local trust data between 1st January 2014 and 31st December 2019. Data from institutions registered for EPPIC was compiled and compared to the national guidelines for adults.

Design

A pragmatic, multicentre, parallel-group, randomised controlled trial to determine whether the intervention is superior to comparator

Setting

20 NHS Hospitals

Methods

We report factors that affect outcome on 526 patients undergoing MAT across two sites (one in the UK and one in Italy). Outcomes of interest were the Knee injury and Osteoarthritis Outcome Score four (KOOS4) at two years and failure rates. We performed multiple regression analysis to examine for factors affecting KOOS, and Cox proportional hazards models for survivorship.

Objectives

Magnetic resonance imaging (MRI) is one of the most widely used investigations for knee pain as it provides detailed assessment of the bone and soft tissues. The aim of this study was to report the frequency of each diagnosis identified on MRI scans of the knee and explore the relationship between MRI results and onward treatment.

Methods

Consecutive MRI reports from a large NHS trust performed in 2017 were included in this study. The hospital electronic system was consulted to identify whether a patient underwent x-ray prior to the MRI, attended an outpatient appointment or underwent surgery.

Methods

We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled trials, and trial registries up to 26 March 2020. We included randomized controlled trials (RCTs), comparing TKA with a tourniquet versus without a tourniquet. Outcomes included: pain, function, serious adverse events (SAEs), blood loss, implant stability, duration of surgery, and length of hospital stay.

Methods

Alignment specific physiological loading was determined using telemetric tibial implant data from Orthoload [2] and applying it to a validated finite element lower limb model developed by the University of Denver [3]. Two high demand activities were selected for the loading section of this study: step down (SD) and deep knee bend (DKB). Using the lower limb model, hip and ankle external boundary conditions were applied to the ATTUNE^® knee system for both MA and AA techniques. The 6 degree of freedom kinetics and kinematics for each activity were then extracted from the model for each alignment type. Mechanical alignment (MA) was considered to be neutral alignment (0° Hip Knee Ankle Angle (HKA), 0° Joint Line (JL)) and AA was chosen to be 3° varus HKA, 5° JL. It is important not to exceed the limits of safety when using AA as such it is noted that DePuy Synthes recommends staying within 3º varus HKA and 3º JL. The use of 5º JL was used in this study to account for surgical variation [Depuy-Synthes surgical technique DSUS/JRC/0617/2179].

Following a similar method described by Maag et al [1] ATTUNE tibial implants were cemented into a bone analog with 2 mL of bone marrow in the distal cavity and an additional reservoir of lipid adjacent to the posterior edge of the implant. Tibial implant constructs were then subjected to intra-operative ROM/stability evaluation, followed by a hyperextension activity until 15 minutes of cement curing time, and finally 3 additional ROM/stability evaluations were performed using an AMTI VIVO simulator. The alignment specific loading parameters were then applied to the tibial implants using an AMTI VIVO simulator. Each sample was subjected to 50,000 DKB cycles and 120,000 SD cycles at 0.8 Hz in series; approximating 2 years of physiological activity. After physiological loading the samples were tested for fixation failure load by axial pull off.

Materials and Methods

Previously reported DKB profiles were developed based on in vivo patellofemoral data and include a wide range of patient variability. The profiles chosen for this body of work were based on the stress in the patellar lateral facet; maximizing this stress whilst maintaining the ability to run the profile stably on the simulator. Load/kinematic profiles were run on three patellar designs (n=3 per group) for 220,000 cycles at 0.8Hz on an AMTI VIVO joint simulator. A comparison cohort of clinically retrieved devices of the same design was identified in an IRB-approved database. Exclusion criteria included gross delamination, cracking secondary to oxidation, and surgeon-reported evidence of malalignment leading to mal-tracking. 29 Patellae were included for analysis: PFC^® All Poly (n=14), ATTUNE^® Anatomic (n=6), and ATTUNE^®Medialized Dome (n=9). Mean in vivo duration was 70.1 months. Patellae were analyzed under optical microscope in large-depth-of-field mode to map the surface damage profile. Burnishing ‘heat-maps’ were generated for retrievals and simulated patellae by normalizing the patellar size and overlaying silhouettes from each component of the same type using a custom-developed MatLAB code.