Aims. Proliferation, migration, and differentiation of anterior cruciate ligament (ACL) remnant and surrounding cells are fundamental processes for ACL reconstruction; however, the interaction between ACL remnant and surrounding cells is unclear. We hypothesized that ACL remnant cells preserve the capability to regulate the surrounding cells’ activity, collagen gene expression, and tenogenic differentiation. Moreover, extracorporeal shock wave (ESW) would not only promote activity of ACL remnant cells, but also enhance their paracrine regulation of surrounding cells. Methods. Cell viability, proliferation, migration, and expression levels of Collagen-I (COL-I) A1, transforming growth factor beta (TGF-β), and vascular endothelial growth factor (VEGF) were compared between ACL remnant cells untreated and treated with ESW (0.15 mJ/mm. 2. , 1,000 impulses, 4 Hz). To evaluate the subsequent effects on the surrounding cells, bone marrow stromal cells (BMSCs)’ viability, proliferation, migration, and levels of Type I Collagen, Type III Collagen, and tenogenic gene (Scx, TNC) expression were investigated using coculture system. Results. ESW-treated ACL remnant cells presented higher cell viability, proliferation, migration, and increased expression of COL-I A1, TGF-β, and VEGF. BMSC proliferation and migration rate significantly increased after coculture with ACL remnant cells with and without ESW stimulation compared to the BMSCs alone group. Furthermore, ESW significantly enhanced ACL remnant cells’ capability to upregulate the collagen gene expression and tenogenic differentiation of BMSCs, without affecting cell viability, TGF-β, and VEGF expression. Conclusion. ACL remnant cells modulated activity and differentiation of surrounding cells. The results indicated that ESW enhanced ACL remnant cells viability, proliferation, migration, and expression of collagen, TGF-β, VEGF, and paracrine regulation of BMSC proliferation, migration, collagen expression, and tenogenesis. Cite this article: Bone Joint Res 2020;9(8):457–467

Aims. Although total knee arthroplasty (TKA) is a highly successful procedure, about 20% of patients remain dissatisfied postoperatively. This proportion is derived from dichotomous models of the assessment of surgical success or failure, which may not reflect the spectrum of outcomes. The aim of this study was to explore differing responses to surgery, and assess whether there are distinct groups of patients with differing patterns of outcome. Methods. This was a secondary analysis of a UK multicentre TKA longitudinal cohort study. We used a group-based trajectory modelling analysis of Oxford Knee Score (OKS) in the first year following surgery with longitudinal data involving five different timepoints and multiple predictor variables. Associations between the derived trajectory groups and categorical baseline variables were assessed, and predictors of trajectory group membership were identified using Poisson regression and multinomial logistic regression, as appropriate. The final model was adjusted for sociodemographic factors (age, sex) and baseline OKS. Results. Data from 731 patients were available for analysis. Three distinct trajectories of outcome were identified: “poor” 14.0%, “modest” 39.1%, and “good” 46.9%. The predicted probability of membership for patients assigned to each trajectory group was high (0.89 to 0.93). Preoperative mental, physical health, and psychosocial factors determined which trajectory is likely to be followed. Poor responders were characterized by a comparatively small number of factors, preoperative expectations of pain and limitations, coping strategies, and a lower baseline physical health status, while the good responders were characterized by a combination of clinical, psychosocial, mental health, and quality of life factors. Conclusion. We identified three distinct response trajectories in patients undergoing TKA. Controlling for baseline score, age, and sex, psychosocial factors such as expectations of pain and limited function and poor coping strategies differentiated the trajectory groups, suggesting a role for preoperative psychosocial support in optimizing the clinical outcome. Cite this article: Bone Joint J 2021;103-B(6):1096–1102

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This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA.

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The metabolic equivalent of task (MET) score examines patient performance in relation to energy expenditure before and after knee arthroplasty. This study assesses its use in a knee arthroplasty population in comparison with the widely used Oxford Knee Score (OKS) and EuroQol five-dimension index (EQ-5D), which are reported to be limited by ceiling effects.

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Implantation of ultra-purified alginate (UPAL) gel is safe and effective in animal osteochondral defect models. This study aimed to examine the applicability of UPAL gel implantation to acellular therapy in humans with cartilage injury.

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The antidiabetic agent metformin inhibits fibrosis in various organs. This study aims to elucidate the effects of hyperglycaemia and metformin on knee joint capsule fibrosis in mice.

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Adenosine, lidocaine, and Mg²⁺ (ALM) therapy exerts differential immuno-inflammatory responses in males and females early after anterior cruciate ligament (ACL) reconstruction (ACLR). Our aim was to investigate sex-specific effects of ALM therapy on joint tissue repair and recovery 28 days after surgery.

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With up to 40% of patients having patellofemoral joint osteoarthritis (PFJ OA), the two arthroplasty options are to replace solely the patellofemoral joint via patellofemoral arthroplasty (PFA), or the entire knee via total knee arthroplasty (TKA). The aim of this study was to assess postoperative success of second-generation PFAs compared to TKAs for patients treated for PFJ OA using patient-reported outcome measures (PROMs) and domains deemed important by patients following a patient and public involvement meeting.

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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.

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Unicompartmental knee arthroplasty (UKA) has higher revision rates than total knee arthroplasty (TKA). As revision of UKA may be less technically demanding than revision TKA, UKA patients with poor functional outcomes may be more likely to be offered revision than TKA patients with similar outcomes. The aim of this study was to compare clinical thresholds for revisions between TKA and UKA using revision incidence and patient-reported outcomes, in a large, matched cohort at early, mid-, and late-term follow-up.

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The diagnosis of periprosthetic joint infection (PJI) can be challenging as the symptoms are similar to other conditions, and the markers used for diagnosis have limited sensitivity and specificity. Recent research has suggested using blood cell ratios, such as platelet-to-volume ratio (PVR) and platelet-to-lymphocyte ratio (PLR), to improve diagnostic accuracy. The aim of the study was to further validate the effectiveness of PVR and PLR in diagnosing PJI.

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Total knee arthroplasty (TKA) may provoke ankle symptoms. The aim of this study was to validate the impact of the preoperative mechanical tibiofemoral angle (mTFA), the talar tilt (TT) on ankle symptoms after TKA, and assess changes in the range of motion (ROM) of the subtalar joint, foot posture, and ankle laxity.

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To map the Oxford Knee Score (OKS) and High Activity Arthroplasty Score (HAAS) items to a common scale, and to investigate the psychometric properties of this new scale for the measurement of knee health.

Introduction. Identifying knee osteoarthritis patient phenotypes is relevant to assessing treatment efficacy. Biomechanical variability has not been applied to phenotyping, yet features may be related to outcomes of total knee arthroplasty (TKA), an inherently mechanical surgery. This study aimed to i) identify biomechanical phenotypes among TKA candidates based on demographic and gait mechanic similarities, and ii) compare objective gait improvements between phenotypes post-TKA. Methods. TKA patients underwent 3D gait analysis one-week pre (n=134) and one-year post-TKA (n=105). Principal component analysis was applied to frontal and sagittal knee angle and moment gait waveforms, extracting major patterns of variability. Demographics (age, sex, BMI), gait speed, and frontal and sagittal pre-TKA angle and moment principal component (PC) scores previously found to differentiate sex, osteoarthritis (OA) severity, and symptoms of TKA recipients were standardized (mean=0, SD=1, [134×15]) to perform multidimensional scaling and machine learning based hierarchical clustering. Final clusters were validated by examining inter-cluster differences at baseline and gait changes (Post. PCscore. –Pre. PCscore. ) by k-way Chi-Squared, and ANOVA tests. Results. Four (k=4) TKA candidate groups yielded optimum clustering metrics, interpreted as 1) high-functioning males, 2) older stiff-kneed males, 3) slower stiff-kneed females, and 4) high-functioning females. Pre-TKA, higher-functioning clusters (1 & 4) had more dynamic loading/un-loading kinetic patterns during stance (flexion moment PC2, 3<2<4<1, P<0.001; adduction moent PC2; 3,2<4<1; P<0.001). Post-TKA, higher-functioning clusters demonstrated less gait improvement (flexion angle ΔPC2, 1,2,4<3, P<0.001; flexion moment ΔPC2, 4<2,3, P<0.001; adduction moment ΔPC2, 1<3, P=0.01). Conclusions. TKA candidates can be characterized by four clusters, interpreted as 1) high-functioning males, 2) older stiff-kneed males, 3) slower stiff-kneed females, and 4) high-functioning females, differing by demographics and biomechanical severity features. Functional gains after TKA were cluster-specific; stiff-gait clusters experienced more improvement, while higher-functioning clusters demonstrated some functional decline. Results suggest the presence of cohorts who may not benefit functionally from TKA. Cluster profiling may aid in triaging and developing osteoarthritis management and surgical strategies that meet individual or group-level function needs. For figures, tables, or references, please contact authors directly

Introduction. Next generation sequencing (NGS) has been shown to facilitate detection of microbes in a clinical sample, particularly in the setting of culture-negative periprosthetic joint infection (PJI). However, it is unknown whether every microbial DNA signal detected by NGS is clinically relevant. This multi-institutional study was conceived to 1) identify species detected by NGS that may predict PJI, then 2) build a predictive model for PJI in a developmental cohort; and 3) validate the predictive utility of the model in a separate multi-institutional cohort. Methods. This multicenter investigation involving 15 academic institutions prospectively collected samples from 194 revision total knee arthroplasties (TKA) and 184 revision hip arthroplasties (THA) between 2017–2019. Patients undergoing reimplantation or spacer exchange procedures were excluded. Synovial fluid, deep tissue and swabs were obtained at the time of surgery and shipped to MicrogenDx (Lubbock, TX) for NGS analysis. Deep tissue specimens were also sent to the institutional labs for culture. All patients were classified per the 2018 Consensus definition of PJI. Microbial DNA analysis of community similarities (ANCOM) was used to identify 17 candidate bacterial species out of 294 (W-value >50) for differentiating infected vs. noninfected cases. Logistic Regression with LASSO model selection and random forest algorithms were then used to build a model for predicting PJI. For this analysis, ICM classification was the response variable (gold standard) and the species identified through ANCOM were the predictor variables. Recruited cases were randomly split in half, with one half designated as the training set, and the other half as the validation set. Using the training set, a model for PJI diagnosis was generated. The optimal resulting model was then tested for prediction ability with the validation set. The entire model-building procedure and validation was iterated 1000 times. From the model set, distributions of overall assignment rate, specificity, sensitivity, positive predictive value (PPV) and negative predicative value (NPV) were assessed. Results. The overall predictive accuracy achieved in the model was 75.9% (Figure 1). There was a high accuracy in true-negative and false-negative classification of patients using this predictive model (Figure 2), which has previously been a criticism of NGS interpretation and reporting. Specificity was 97.1%, PPV was 75.0%, and NPV was 76.2%. On comparison of the distribution of abundances between ICM-positive and ICM-negative patients, Staphylococcus aureus was the strongest contributor (F=0.99) to the predictive power of the model (Figure 3). In contrast, Cutibacterium acnes was less predictive (F=0.309) and noted to be abundant across both infected and noninfected revision TJA samples. Discussion. This study is the first to utilize predictive modeling algorithms on a large prospective multicenter database in order to transform analytic NGS data into a clinically relevant diagnostic signal. Our collaborative findings suggest the microbial DNA signal identified on NGS may be an independent useful adjunct for the diagnosis of PJI, as well as help identify causative organisms. Further work applying artificial intelligence tools will improve accuracy, predictive power and clinical utility of high-throughput sequencing technology. For figures, tables, or references, please contact authors directly

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Thresholds of acceptable early migration of the components in total knee arthroplasty (TKA) have traditionally ignored the effects of patient and implant factors that may influence migration. The aim of this study was to determine which of these factors are associated with overall longitudinal migration of well-fixed tibial components following TKA.

Hyaline cartilage defects are a significant clinical problem for which a plethora of cartilage repair techniques are used. One such technique is cartilage replacement therapy using autologous chondrocyte or mesenchymal stem cell (MSC) implantation (ACI). Mesenchymal stem cells are increasingly being used for these types of repair technique because they are relatively easy to obtain and can be expanded to generate millions of cells. However, implanted MSCs can terminally differentiate and produce osteogenic tissue which is highly undesirable, also, MSCs generally only produce fibrocartilage which does not make biomechanically resilient repair tissue, an attribute that is crucial in high weight-bearing areas. Tissue-specific adult stem cells would be ideal candidates to fill the void, and as we have shown previously in animal model systems [Dowthwaite et al, 2004, J Cell Sci 117;889], they can be expanded to generate hundreds of millions of cells, produce hyaline cartilage and they have a restricted differential potential. Articular chondroprogenitors do not readily terminally differentiate down the osteogenic lineage. At present, research focused on isolating tissue-specific stem cells from articular cartilage has met with modest success. Our results demonstrate that using differential adhesion it is possible to easily isolate articular cartilage progenitor populations from human hyaline cartilage and that these cells can be subsequently expanded in vitro to a high population doubling whilst maintaining a normal karyotype. Articular cartilage progenitors maintain telomerase activity and telomere length that are a characteristic of progenitor/stem cells and differentiate to produce hyaline cartilage. In conclusion, we propose the identification and characterisation of a novel articular cartilage progenitor population, resident in human cartilage, which will greatly benefit future cell-based cartilage repair therapies

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Despite recent literature questioning their use, vancomycin and clindamycin often substitute cefazolin as the preoperative antibiotic prophylaxis in primary total knee arthroplasty (TKA), especially in the setting of documented allergy to penicillin. Topical povidone-iodine lavage and vancomycin powder (VIP) are adjuncts that may further broaden antimicrobial coverage, and have shown some promise in recent investigations. The purpose of this study, therefore, is to compare the risk of acute periprosthetic joint infection (PJI) in primary TKA patients who received cefazolin and VIP to those who received a non-cephalosporin alternative and VIP.

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Simultaneous bilateral total knee arthroplasty (TKA) has been used due to its financial advantages, overall resource usage, and convenience for the patient. The training model where a trainee performs the first TKA, followed by the trainer surgeon performing the second TKA, is a unique model to our institution. This study aims to analyze the functional and clinical outcomes of bilateral simultaneous TKA when performed by a trainee or a supervising surgeon, and also to assess these outcomes based on which side was done by the trainee or by the surgeon.

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Current guidelines consider analyses of joint aspirates, including leucocyte cell count (LC) and polymorphonuclear percentage (PMN%) as a diagnostic mainstay of periprosthetic joint infection (PJI). It is unclear if these parameters are subject to a certain degree of variability over time. Therefore, the aim of this study was to evaluate the variation of LC and PMN% in patients with aseptic revision total knee arthroplasty (TKA).