This study aims to identify the top unanswered research priorities in the field of knee surgery using consensus-based methodology. Initial research questions were generated using an online survey sent to all 680 members of the British Association for Surgery of the Knee (BASK). Duplicates were removed and a longlist was generated from this scoping exercise by a panel of 13 experts from across the UK who provided oversight of the process. A modified Delphi process was used to refine the questions and determine a final list. To rank the final list of questions, each question was scored between one (low importance) and ten (high importance) in order to produce the final list.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
Electromagnetic induction heating has demonstrated in vitro antibacterial efficacy over biofilms on metallic biomaterials, although no in vivo studies have been published. Assessment of side effects, including thermal necrosis of adjacent tissue, would determine transferability into clinical practice. Our goal was to assess bone necrosis and antibacterial efficacy of induction heating on biofilm-infected implants in an in vivo setting. Titanium-aluminium-vanadium (Ti6Al4V) screws were implanted in medial condyle of New Zealand giant rabbit knee. Study intervention consisted of induction heating of the screw head up to 70°C for 3.5 minutes after implantation using a portable device. Both knees were implanted, and induction heating was applied unilaterally keeping contralateral knee as paired control. Sterile screws were implanted in six rabbits, while the other six received screws coated with Aims
Methods
This multicentre retrospective observational study’s aims were to investigate whether there are differences in the occurrence of radiolucent lines (RLLs) following total knee arthroplasty (TKA) between the conventional Attune baseplate and its successor, the novel Attune S+, independent from other potentially influencing factors; and whether tibial baseplate design and presence of RLLs are associated with differing risk of revision. A total of 780 patients (39% male; median age 70.7 years (IQR 62.0 to 77.2)) underwent cemented TKA using the Attune Knee System) at five centres, and with the latest radiograph available for the evaluation of RLL at between six and 36 months from surgery. Univariate and multivariate logistic regression models were performed to assess associations between patient and implant-associated factors on the presence of tibial and femoral RLLs. Differences in revision risk depending on RLLs and tibial baseplate design were investigated with the log-rank test.Aims
Methods
For displaced femoral neck fractures (FNFs) in geriatric patients, there remains uncertainty regarding the effect of total hip arthroplasty (THA) compared with hemiarthroplasty (HA) in the guidelines. We aimed to compare 90-day surgical readmission, in-hospital complications, and charges between THA and HA in these patients. The Hospital Quality Monitoring System was queried from 1 January 2013 to 31 December 2019 for displaced FNFs in geriatric patients treated with THA or HA. After propensity score matching, which identified 33,849 paired patients, outcomes were compared between THA and HA using logistic and linear regression models.Aims
Methods
The December 2023 Research Roundup360 looks at: Tissue integration and chondroprotective potential of acetabular labral augmentation with autograft tendon: study of a porcine model; The Irish National Orthopaedic Register under cyberattack: what happened, and what were the consequences?; An overview of machine learning in orthopaedic surgery: an educational paper; Beware of the fungus…; New evidence for COVID-19 in patients undergoing joint replacement surgery.
In 2017, the British Society for Children’s Orthopaedic Surgery engaged the profession and all relevant stakeholders in two formal research prioritization processes. In this editorial, we describe the impact of this prioritization on funding, and how research in children’s orthopaedics, which was until very recently a largely unfunded and under-investigated area, is now flourishing. Establishing research priorities was a crucial step in this process. Cite this article:
Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered. Cite this article:
The February 2023 Knee Roundup360 looks at: Machine-learning models: are all complications predictable?; Positive cultures can be safely ignored in revision arthroplasty patients that do not meet the 2018 International Consensus Meeting Criteria; Spinal versus general anaesthesia in contemporary primary total knee arthroplasty; Preoperative pain and early arthritis are associated with poor outcomes in total knee arthroplasty; Risk factors for infection and revision surgery following patellar tendon and quadriceps tendon repairs; Supervised versus unsupervised rehabilitation following total knee arthroplasty; Kinematic alignment has similar outcomes to mechanical alignment: a systematic review and meta-analysis; Lifetime risk of revision after knee arthroplasty influenced by age, sex, and indication; Risk factors for knee osteoarthritis after traumatic knee injury.
