Aims. The diagnosis of periprosthetic joint infection (PJI) continues to present a significant clinical challenge. New biomarkers have been proposed to support clinical decision-making; among them, synovial fluid alpha-defensin has gained interest. Current research methodology suggests reference methods are needed to establish solid evidence for use of the test. This prospective study aims to evaluate the diagnostic accuracy of high-performance liquid chromatography coupled with the mass spectrometry (LC-MS) method to detect alpha-defensin in synovial fluid. Methods. Between October 2017 and September 2019, we collected synovial fluid samples from patients scheduled to undergo revision surgery for painful total knee arthroplasty (TKA). The International Consensus Meeting criteria were used to classify 33 PJIs and 92 aseptic joints. LC-MS assay was performed to measure alpha-defensin in synovial fluid of all included patients. Sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve (AUC) were calculated to define the test diagnostic accuracy. Results. The AUC was 0.99 (95% confidence interval (CI) 0.98 to 1.00). Receiver operating characteristic (ROC) analysis showed that the optimal cut-off value of synovial fluid alpha-defensin was 1.0 μg/l. The sensitivity of alpha-defensin was 100% (95% CI 96 to 100), the specificity was 97% (95% CI 90 to 98), the positive predictive value was 89.2% (95% CI 82 to 94), and negative predictive value was 100% (95% CI 96 to 100). ROC analysis demonstrated an AUC of 0.99 (95% CI 0.98 to 1.0). Conclusion. The present study confirms the utility of alpha-defensin in the synovial fluid in patients with painful TKA to select cases of PJI. Since LC-MS is still a time-consuming technology and is available in highly specialized laboratories, further translational research studies are needed to take this evidence into routine procedures and promote a new diagnostic approach. Cite this article: Bone Joint J 2022;104-B(9):1047–1051

Abstract. Background. Prosthetic joint infection (PJI) is a significant cause of morbidity and mortality following knee replacement surgery. Identifying the causative agent(s) and their antibiotic sensitivities is critical in determining the choice of treatment methods used and the likelihood of successful eradication. This study aimed to investigate:. Whether biopsy alone was superior to aspiration alone in specificity and sensitivity for diagnosing PJI following knee replacement. Whether biopsy identifies the same microbiological flora as aspiration. Methods. We identified consecutive patients passing through our knee infection Multi-Disciplinary Team meeting between December 2014 and March 2020. Data was collated data retrospectively using electronic records. Statistical analysis was performed using Stata (Timberlake, February 2020). Results. 65 of 100 patients identified had both pre-operative aspiration and biopsy. In 29% of positive patients, biopsy identified new or additional organisms not previously identified by aspiration. Aspiration had a sensitivity of 70%, specificity of 88%, positive predictive value of 90.3% and negative predictive value of 64.7%. Biopsy had a sensitivity of 97.5%, specificity of 88%, positive predictive value of 92.9% and negative predictive value of 95.7%. Conclusion. Biopsy is superior to aspiration in the diagnosis of PJI and can be performed safely and successfully. It identifies organisms when aspiration may be negative and identifies additional microorganisms in a polymicrobial setting not identified by aspiration alone (29% of positive cases). We would recommend, where possible, aspiration and biopsy as routine pre-operative sampling in order to identify all causative agents and their susceptibilities prior to embarking on revision surgery

We analysed the serum C-reactive protein level, synovial fluid obtained by joint aspiration and five synovial biopsies from 145 knee replacements prior to revision to assess the value of these parameters in diagnosing late peri-prosthetic infection. Five further synovial biopsies were used for histological analysis. Samples were also obtained during the revision and incubated and analysed in an identical manner for 14 days. A total of 40 total knee replacements were found to be infected (prevalence 27.6%). The aspiration technique had a sensitivity of 72.5% (95% confidence interval (CI) 58.7 to 86.3), a specificity of 95.2% (95% CI 91.2 to 99.2), a positive predictive value of 85.3% (95% CI 73.4 to 100), a negative predictive value of 90.1% (95% CI 84.5 to 95.7) and an accuracy of 89%. The biopsy technique had a sensitivity of 100%, a specificity of 98.1% (95% CI 95.5 to 100), a positive predictive value of 95.2% (95% CI 88.8 to 100), a negative predictive value of 100% and an accuracy of 98.6%. C-reactive protein with a cut-off-point of 13.5 mg/l had a sensitivity of 72.5% (95% CI 58.7 to 86.3), a specificity of 80.9% (95% CI 73.4 to 88.4), a positive predictive value of 59.2% (95% CI 45.4 to 73.0), a negative predictive value of 88.5% (95% 81.0 to 96.0 CI) and an accuracy of 78.1%. We found that biopsy was superior to joint aspiration and C-reactive protein in the diagnosis of late peri-prosthetic infection of total knee replacements

Abstract. Introduction. Failing total knee replacement management has included isotope bone scan to identify infection or loosening. BASK guidance suggests bone scans have a poor positive predictive value and are not advised. We assessed isotope bone scanning as a negative predictor to exclude loosening or infection in failing total knee replacement. Methodology. Retrospective review of consecutive bone scans performed to investigate painful total knee replacements for a one-year period (June 2017 to June 2018). 166 bone scans performed. 33 excluded (no notes or scan for other reasons). Demographic information, age of prosthesis, clinic review date, serological markers, results of aspiration and subsequent intraoperative findings also recorded. Results. 133 patients, mean age 72.7, average age of prosthesis 6.8 years. 45% scans performed showed evidence of infection or loosening. Of those positive scans, 70% had aspiration and consideration for revision surgery. 73 patients had negative scans. 2 patients had subsequent aspiration and in 1 patient, S. Epidermidis isolated (1 patient had patellar revision and further samples clear of and other patient declined further surgery). Conclusion. Isotope bone scan had a 97.2% negative predictive value making it a very useful tool to evaluate the failing knee replacement and exclude significant loosening or infection

The diagnosis of a meniscal tear may require MRI, which is costly. Ultrasonography has been used to image the meniscus, but there are no reliable data on its accuracy. We performed a prospective study investigating the sensitivity and specificity of ultrasonography in comparison with MRI; the final outcome was determined at arthroscopy. The study included 35 patients with a mean age of 47 years (14 to 73). There was a sensitivity of 86.4% (95% confidence interval (CI) 75 to 97.7), a specificity of 69.2% (95% CI 53.7 to 84.7), a positive predictive value of 82.6% (95% CI 70 to 95.2) and a negative predictive value of 75% (95% CI 60.7 to 81.1) for ultrasonography. This compared favourably with a sensitivity of 86.4% (95% CI 75 to 97.7), a specificity of 100.0%, a positive predictive value of 100.0% and a negative predictive value of 81.3% (95% CI 74.7 to 87.9) for MRI. Given that the sensitivity matched that of MRI we feel that ultrasonography can reasonably be applied to confirm the clinical diagnosis before undertaking arthroscopy. However, the lower specificity suggests that there is still a need to improve the technique to reduce the number of false-positive diagnoses and thus to avoid unnecessary arthroscopy

Aims. Hereditary haemochromatosis is a genetic disorder that is caused by several known mutations in the human homeostatic iron regulator protein (HFE) gene. Abnormal accumulation of iron causes a joint disease that resembles osteoarthritis (OA), but appears at a relatively younger age and is accompanied by cirrhosis, diabetes, and injury to other organs. Increased serum transferrin saturation and ferritin levels are known markers of haemochromatosis with high positive predictive values. Methods. We have retrospectively analyzed the iron studies of a cohort of 2,035 patients undergoing knee joint arthroplasty due to OA. Results. No patients had HFE gene C282Y, S65C, or H63D mutations testing. In total, 18 patients (2.96%) of the male cohort and 51 (3.58%) of the female cohort had pathologically increased ferritin levels that may be indicative of haemochromatosis. Seven patients (0.34%) had serum transferrin saturation above 45%. Conclusion. The awareness for the diagnosis of this disorder in Orthopaedics is low and needs improvement. Osteoarthritic patients undergoing knee arthroplasty should be routinely screened for haemochromatosis by iron studies and referred to genetic testing when needed. Level of evidence: Level III - Retrospective cohort study. Cite this article: Bone Jt Open 2021;2(12):1062–1066

Aims. Although knee osteoarthritis (OA) is diagnosed and monitored radiologically, actual full-thickness cartilage loss (FTCL) has rarely been correlated with radiological classification. This study aims to analyze which classification system correlates best with FTCL and to assess their reliability. Methods. A prospective study of 300 consecutive patients undergoing unilateral total knee arthroplasty (TKA) for OA (mean age 69 years (44 to 91; standard deviation (SD) 9.5), 178 (59%) female). Two blinded examiners independently graded preoperative radiographs using five common systems: Kellgren-Lawrence (KL); International Knee Documentation Committee (IKDC); Fairbank; Brandt; and Ahlbäck. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC). Intraoperatively, anterior cruciate ligament (ACL) status and the presence of FTCL in 16 regions of interest were recorded. Radiological classification and FTCL were correlated using the Spearman correlation coefficient. Results. Knees had a mean of 6.8 regions of FTCL (SD 3.1), most common medially. The commonest patterns of FTCL were medial ± patellofemoral (143/300, 48%) and tricompartmental (89/300, 30%). ACL status was associated with pattern of FTCL (p = 0.023). All radiological classification systems demonstrated moderate ICC, but this was highest for the IKDC: whole knee 0.68 (95% confidence interval (CI) 0.60 to 0.74); medial compartment 0.84 (95% CI 0.80 to 0.87); and lateral compartment 0.79 (95% CI 0.73 to 0.83). Correlation with actual FTCL was strongest for Ahlbäck (Spearman rho 0.27 to 0.39) and KL (0.30 to 0.33) systems, although all systems demonstrated medium correlation. The Ahlbäck score was the most discriminating in severe knee OA. Osteophyte presence in the medial compartment had high positive predictive value (PPV) for FTCL, but not in the lateral compartment. Conclusion. The Ahlbäck and KL systems had the highest correlation with confirmed cartilage loss at TKA. However, the IKDC system displayed the best interobserver reliability, with favourable correlation with FTCL in medial and lateral compartments, although it was less discriminating in more severe disease. Cite this article: Bone Joint J 2020;102-B(3):301–309

Introduction. Implementing operative eligibility thresholds based on body mass index (BMI) alone risks restricting access to improved pain, function, and quality-of-life. The purpose of this study was to: 1) investigate the relationship between BMI and improvements in 1-year patient reported outcome measures (PROMs), and 2) determine how many patients would have been denied 1-year improvements with specific BMI cut-offs. Methods. Data were collected on a prospective cohort of 3,214 TKA patients from 2015–2018. Clinically meaningful 1-year improvements were defined as 15 points for Knee Injury and Osteoarthritis Outcome Scores (KOOS) pain and Physical Function Shortform (PS), and 14 points for Knee-Related Quality-of-Life (KRQOL). For specific BMI cut-offs, the positive predictive value for predicting a failure to improve and number of patients denied surgery to avoid one failed improvement was calculated. Results. PROMs improvements were greater with increasing BMI. Patients with BMI ≥40 kg/m. 2. had median (Q1, Q3) KOOS pain improvements of 47.2 points (33.3, 58.3) and those with BMI 18.5–24.9 kg/m. 2. had median improvements of 41.7 (27.8, 55.6). Similar findings were observed for KOOS PS (28.4 vs. 26.3) and KRQOL (50.0 vs. 43.8). With a BMI cut-off of 30 kg/m. 2. , 9 patients would have been denied improvements from surgery for each failed improvement avoided whereas with a BMI cut-off of 50 kg/m. 2. , 15 patients would have been denied improvements from surgery. Implementing BMI thresholds alone did not influence the rate of improvements in KOOS-PS or KRQOL. Conclusion. Patients with higher BMI were observed to have greater improvements in PROMs after primary TKA. Enforcing arbitrary BMI cut-offs would deprive pain and functional improvements from patients who would benefit the most. Moreover, there appears to be no increase in the rate of PROMs improvements by enforcing BMI thresholds. This study demonstrates that determining TKA eligibility should involve a holistic approach rather than limiting to BMI measurements alone

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

Introduction. Despite several preventive strategies, periprosthetic joint infection (PJI) following total joint arthroplasty (TJA) is still a devastating complication. Early diagnosis and appropriate treatment are crucial to achieve successful infection control, but challenging since there is no test with 100% sensitivity and 100%. Therefore, several national and international guidelines include synovial analysis of joint aspirates as important diagnostic criteria, but cut-off levels for synovial cell count (CC) and polymorphonuclear (granulocyte) percentage (PMN%) are still debatable. The current investigation was performed to analyze the overall accuracy and optimal cut-off of synovial CC and PMN% following total knee (TKA) and total hip arthroplasty (THA). Methods. Between October 2012 and June 2017, all patients with painful TKA or THA, who underwent joint aspiration before revision arthroplasty were included in this retrospective study. From aspirated synovial fluid, leukocyte esterase activity, leukocyte CC and PMN% were determined, and specimens were sent for bacterial culture. A total of 524 preoperative joint aspirations (255 hips, 269 knees) were enrolled for final analysis. For 337 patients, the synovial CC and PMN% could be measured by the laboratory. From those patients, 203 patients were scheduled for aseptic revision, and 134 patients for septic revision arthroplasty according to the MSIS criteria for PJI. Specificity (SP), sensitivity (SE), positive predictive value (PPV), negative predictive and overall accuracy were measured for CC and PMN%. The optimum cut-off value was calculated by the ROC and the value giving the AUC, achieving the best possible level of sensitivity and specificity. Results. The best cut-off level for PJI of all study patients was 2582 leukocytes/μL (Se 80.6%, Sp 85.2%) and a PMN% of 66.1% (Se 80.6%, Sp 83.3%). The chosen cut-off levels for PJI of TKA was 1630 leukocytes/μL (Se 83.6%, Sp 82.2%) and a PMN% of 60.5% (Se 80.3%, Sp 77.1%). The optimal cut-off values for PJI of THA was 3063 leukocytes/μL (Se 78.1%, Sp 80.0%) and a PMN% of 66.1% (Se 82.2%, Sp 82.4%). Conclusions. Synovial cell count and polymorphonuclear percentage are sensitive methods for diagnosing PJI with differences in cut-off levels for THA and TKA. We suggest considering the cut-off levels of CC and PMN% from aspirates of TKA at 1600/μL and 60%, respectively, as possible PJI. For THA, the cut-off levels of CC and PMN% are at 3000/μL and 66%, respectively

Introduction. Infection after total joint arthroplasty is a challenging problem. Clinical symptoms, Erythrocyte sedimentation rate, C-reactive protein level, and cultures of synovial fluid obtained by means of percutaneous aspiration are commonly used to rule out the possibility of persistent infection before reimplantation. However, the sensitivity and specificity of the tests are low. Some authors have suggested that frozen-section analysis should always be performed during the reimplantation in order to rule out persistent infection. Methods. Retrospective review of 126 revision hip and knee arthroplasty procedure performed from 2002 - 2007 in Derriford Hospital, Plymouth NHS truts, UK. Frozen section was performed in 86 procedures out of the 126 procedures reviewed(68.2 %). A positive frozen section with more than 10 PNLs per HPF was compared with intra operative cultures results. The preoperative CRP results were recorded as well. Results. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy for frozen section were 45.5 %, 93.1%,50%, 95%, 94% respectively. Combining the intraoperative frozen section with the CRP results, the specificity was 100%. Discussion. A negative finding on intra operative analysis of frozen sections has a high predictive value with regard to ruling out the presence of infection; However, the sensitivity of the test for the detection of persistent infection is low. The data support the conclusion that the Frozen Section is reasonably specific but not a sensitive. Combining it with the preoperative CRP results led to increasing the specificity to 100% in our series

Involvement of Patellofemoral joint (PFJ) has significant bearing in the management of osteoarthritis of the knee. The aim of this study is to assess the relationship between skyline radiographs, MRI and arthroscopic findings in the patellofemoral joint. Data was collected prospectively from fifty-three patients who underwent arthroscopy. There were 36 males and 17 females in the group with mean age of 48 years (range 18-71). Arthroscopically PFJ arthritis was classified based on Outerbridge grading system. Patients with Outerbridge grade III and IV lesions were considered to have significant arthritis of the PFJ. Kellgren-Lawrence grading system was used to assess the skyline radiographs. Radiographically patients with grade III and IV Kelgren-Lawrence changes were considered to have significant osteoarthritis of the PFJ. MRI scans were also studied to assess involvement of PFJ. Thirty-two patients had MRI scan and 20 patients had skyline views done as part of preoperative work up. Arthroscopic findings were considered as gold standard. MRI scan had specificity of 75%, sensitivity of 81%, positive predictive value of (PPV) 77 and negative predictive value of (NPV) 80% in diagnosing significant PFJ arthritis. Skyline radiographs had specificity of 100%, sensitivity of 50%, PPV of 100% and NPV of 57%. The overall accuracy of skyline radiographs in predicting significant PFJ arthritis was 70% and for MRI was 78%. We conclude that skyline radiographs has some value in he diagnosis of PFJ arthritis, however the sensitivity and negative predictive value is very is poor

Aims

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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The aim of this study is to compare the effectiveness and safety of thromboprophylactic treatments in patients undergoing primary total knee arthroplasty (TKA).

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This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA).

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It remains difficult to diagnose early postoperative periprosthetic joint infection (PJI) following total knee arthroplasty (TKA). We aimed to validate the optimal cutoff values of ESR, CRP, and synovial fluid analysis for detecting early postoperative PJI in a large series of primary TKAs.

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In patients with a “dry” aspiration during the investigation of prosthetic joint infection (PJI), saline lavage is commonly used to obtain a sample for analysis. The aim of this study was to investigate prospectively the impact of saline lavage on synovial fluid analysis in revision arthroplasty.

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This study aims to determine the proportion of patients with end-stage knee osteoarthritis (OA) possibly suitable for partial (PKA) or combined partial knee arthroplasty (CPKA) according to patterns of full-thickness cartilage loss and anterior cruciate ligament (ACL) status.

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The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance.

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The introduction of a novel design of total knee arthroplasty (TKA) must achieve outcomes at least as good as existing designs. A novel design of TKA with a reducing radius of the femoral component and a modified cam-post articulation has been released and requires assessment of the fixation to bone. Radiostereometric analysis (RSA) of the components within the first two postoperative years has been shown to be predictive of medium- to long-term fixation. The aim of this study was to assess the stability of the tibial component of this system during this period of time using RSA.