Periprosthetic joint infection (PJI) represents a complex challenge in orthopaedic surgery associated with substantial morbidity and healthcare expenditures. The debridement, antibiotics, and implant retention (DAIR) protocol is a viable treatment, offering several advantages over exchange arthroplasty. With the evolution of treatment strategies, considerable efforts have been directed towards enhancing the efficacy of DAIR, including the development of a phased debridement protocol for acute PJI management. This article provides an in-depth analysis of DAIR, presenting the outcomes of single-stage, two-stage, and repeated DAIR procedures. It delves into the challenges faced, including patient heterogeneity, pathogen identification, variability in surgical techniques, and antibiotics selection. Moreover, critical factors that influence the decision-making process between single- and two-stage DAIR protocols are addressed, including team composition, timing of the intervention, antibiotic regimens, and both anatomical and implant-related considerations. By providing a comprehensive overview of DAIR protocols and their clinical implications, this annotation aims to elucidate the advancements, challenges, and potential future directions in the application of DAIR for PJI management. It is intended to equip clinicians with the insights required to effectively navigate the complexities of implementing DAIR strategies, thereby facilitating informed decision-making for optimizing patient outcomes. Cite this article:
Aims. Day-case knee and hip replacement, in which patients are discharged on the day of surgery, has been gaining popularity during the last two decades, and particularly since the COVID-19 pandemic. This systematic review presents the evidence comparing day-case to inpatient-stay surgery. Methods. A systematic literature search was performed of MEDLINE, Embase, and grey literature databases to include all studies which compare day-case with inpatient knee and hip replacement. Meta-analyses were performed where appropriate using a random effects model. The protocol was registered prospectively (PROSPERO CRD42023392811). Results. A total of 38 studies were included, with a total of 83,888 day-case procedures. The studies were predominantly from the USA and Canada, observational, and with a high risk of bias. Day-case patients were a mean of 2.08 years younger (95% CI 1.05 to 3.12), were more likely to be male (odds ratio (OR) 1.3 (95% CI 1.19 to 1.41)), and had a lower mean BMI and American Society of Anesthesiologists grades compared with inpatients. Overall, day-case surgery was associated with significantly lower odds of readmission (OR 0.83 (95% CI 0.73 to 0.96); p = 0.009), subsequent emergency department attendance (OR 0.62 (95% CI 0.48 to 0.79); p < 0.001), and complications (OR 0.7 (95% CI 0.55 to 0.89) p = 0.004), than inpatient surgery. There were no significant differences in the rates of reoperation or mortality. The overall rate of successful same-day discharge for day-case surgery was 85% (95% CI 81 to 88). Patient-reported outcome measures and cost-effectiveness were either equal or favoured day-case. Conclusion. Within the limitations of the literature, in particular the substantial risk of selection bias, the outcomes following day-case knee and hip replacement appear not to be inferior to those following an inpatient stay. The evidence is more robust for
The influence of metabolic syndrome (MetS) on the outcome after hip and knee arthroplasty is debated. We aimed to investigate the change in patient-reported outcome measure (PROM) scores after hip and knee arthroplasty, comparing patients with and without MetS. From 1 May 2017 to 30 November 2019, a prospective cohort of 2,586 patients undergoing elective unilateral hip and knee arthroplasty was established in Denmark. Data from national registries and a local database were used to determine the presence of MetS. Patients’ scores on Oxford Hip Score (OHS) or Oxford Knee Score (OKS), EuroQol five-dimension five-level questionnaire (EQ-5D-5L), University of California, Los Angeles (UCLA) Activity Scale, and Forgotten Joint Score (FJS) at baseline, three, 12, and 24 months after surgery were collected. Primary outcome was the difference between groups from baseline to 12 months in OHS and OKS. Secondary outcomes were scores of OHS and OKS at three and 24 months and EQ-5D-5L, UCLA Activity Scale, and FJS at three, 12, and 24 months after surgery. Generalized linear mixed model was applied, adjusting for age, sex, Charlson Comorbidity Index, and smoking to present marginal mean and associated 95% CIs.Aims
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The optimal bearing surface design for medial unicompartmental knee arthroplasty (UKA) remains controversial. The aim of this study was to compare outcomes of fixed-bearing (FB) and mobile-bearing (MB) UKAs from a single high-volume institution. Prospectively collected data were reviewed for all primary cemented medial UKAs performed by seven surgeons from January 2006 to December 2022. A total of 2,999 UKAs were identified, including 2,315 FB and 684 MB cases. The primary outcome measure was implant survival. Secondary outcomes included 90-day and cumulative complications, reoperations, component revisions, conversion arthroplasties, range of motion, and patient-reported outcome measures. Overall mean age at surgery was 65.7 years (32.9 to 94.3), 53.1% (1,593/2,999) of UKAs were implanted in female patients, and demographics between groups were similar (p > 0.05). The mean follow-up for all UKAs was 3.7 years (0.0 to 15.6).Aims
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Aims. Robotic arm-assisted surgery offers accurate and reproducible guidance in component positioning and assessment of soft-tissue tensioning during knee arthroplasty, but the feasibility and early outcomes when using this technology for revision surgery remain unknown. The objective of this study was to compare the outcomes of robotic arm-assisted revision of
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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Breast cancer survivors have known risk factors that might influence the results of total hip arthroplasty (THA) or total knee arthroplasty (TKA). This study evaluated clinical outcomes of patients with breast cancer history after primary THA and TKA. Our total joint registry identified patients with breast cancer history undergoing primary THA (n = 423) and TKA (n = 540). Patients were matched 1:1 based upon age, sex, BMI, procedure (hip or knee), and surgical year to non-breast cancer controls. Mortality, implant survival, and complications were assessed via Kaplan-Meier methods. Clinical outcomes were evaluated via Harris Hip Scores (HHSs) or Knee Society Scores (KSSs). Mean follow-up was six years (2 to 15).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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This study aimed to investigate patients’ attitudes towards day-case hip and knee arthroplasty and to describe patient characteristics associated with different attitudes, with the purpose of providing an insight into the information requirements for patients that surgeons should address when informing patients about day-case surgery. A total of 5,322 patients scheduled for hip or knee arthroplasty between 2016 and 2022 were included in the study. Preoperatively, patients were asked if they were interested in day-case surgery (‘Yes’, ‘Do not know’, ‘No’). Patient demographics including age, BMI, sex, and patient-reported outcome measures (PROMs) such as the EuroQol five-dimension three-level questionnaire (EQ-5D-3L) were examined within each attitude group. Additionally, changes in attitude were assessed among patients who had completed the questionnaire in association with prior hip or knee arthroplasty.Aims
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Total hip and knee arthroplasty (THA, TKA) are largely successful procedures; however, both have variable outcomes, resulting in some patients being dissatisfied with the outcome. Surgeons are turning to technologies such as robotic-assisted surgery in an attempt to improve outcomes. Robust studies are needed to find out if these innovations are really benefitting patients. The Robotic Arthroplasty Clinical and Cost Effectiveness Randomised Controlled Trials (RACER) trials are multicentre, patient-blinded randomized controlled trials. The patients have primary osteoarthritis of the hip or knee. The operation is Mako-assisted THA or TKA and the control groups have operations using conventional instruments. The primary clinical outcome is the Forgotten Joint Score at 12 months, and there is a built-in analysis of cost-effectiveness. Secondary outcomes include early pain, the alignment of the components, and medium- to long-term outcomes. This annotation outlines the need to assess these technologies and discusses the design and challenges when conducting such trials, including surgical workflows, isolating the effect of the operation, blinding, and assessing the learning curve. Finally, the future of robotic surgery is discussed, including the need to contemporaneously introduce and evaluate such technologies. Cite this article:
The primary aim was to assess change in health-related quality of life (HRQoL) of patients as they waited from six to 12 months for a total hip (THA) or total or partial knee arthroplasty (KA). Secondary aims were to assess change in joint-specific function, mental health, quality of sleep, number living in a state worse than death (WTD), wellbeing, and patient satisfaction with their healthcare. This prospective study included 142 patients awaiting a THA (mean age 66.7 years (SD 11.4); 71 female) and 214 patients awaiting KA (mean age 69.7 years (SD 8.7); 117 female). Patients completed questionnaires (EuroQol five-dimension health questionnaire (EQ-5D), Oxford Hip and Knee Scores (OHS/OKS), Pittsburgh Sleep Quality Index (PSQI), Hospital Anxiety and Depression Score (HADS), University of California, Los Angeles Activity Scale, wellbeing assessment, and satisfaction with their healthcare) at six and 12 months while awaiting surgery.Aims
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Periprosthetic fractures (PPFs) around the knee are challenging injuries. This study aims to describe the characteristics of knee PPFs and the impact of patient demographics, fracture types, and management modalities on in-hospital mortality. Using a multicentre study design, independent of registry data, we included adult patients sustaining a PPF around a knee arthroplasty between 1 January 2010 and 31 December 2019. Univariate, then multivariable, logistic regression analyses were performed to study the impact of patient, fracture, and treatment on mortality.Aims
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Aims. The aim of this study was to evaluate the association between chondral injury and interval from anterior cruciate ligament (ACL) tear to surgical reconstruction (ACLr). Methods. Between January 2012 and January 2022, 1,840 consecutive ACLrs were performed and included in a single-centre retrospective cohort. Exclusion criteria were partial tears, multiligament knee injuries, prior ipsilateral knee surgery, concomitant
Aims.
In the last decade, perioperative advancements have expanded the use of outpatient primary total knee arthroplasty (TKA). Despite this, there remains limited data on expedited discharge after revision TKA. This study compared 30-day readmissions and reoperations in patients undergoing revision TKA with a hospital stay greater or less than 24 hours. The authors hypothesized that expedited discharge in select patients would not be associated with increased 30-day readmissions and reoperations. Aseptic revision TKAs in the National Surgical Quality Improvement Program database were reviewed from 2013 to 2020. TKAs were stratified by length of hospital stay (greater or less than 24 hours). Patient demographic details, medical comorbidities, American Society of Anesthesiologists (ASA) grade, operating time, components revised, 30-day readmissions, and reoperations were compared. Multivariate analysis evaluated predictors of discharge prior to 24 hours, 30-day readmission, and reoperation.Aims
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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:
Aims. A fracture of the medial tibial plateau is a serious complication of Oxford mobile-bearing
Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are common orthopaedic procedures requiring postoperative radiographs to confirm implant positioning and identify complications. Artificial intelligence (AI)-based image analysis has the potential to automate this postoperative surveillance. The aim of this study was to prepare a scoping review to investigate how AI is being used in the analysis of radiographs following THA and TKA, and how accurate these tools are. The Embase, MEDLINE, and PubMed libraries were systematically searched to identify relevant articles. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews and Arksey and O’Malley framework were followed. Study quality was assessed using a modified Methodological Index for Non-Randomized Studies tool. AI performance was reported using either the area under the curve (AUC) or accuracy.Aims
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