No single test has demonstrated absolute accuracy in the diagnosis of periprosthetic joint infection (PJI). Leukocyte esterase (LE) is a synovial marker that has proven utility in the diagnosis of PJI. The purpose of this prospective study was to (1) identify the optimal cutoff for the use of LE in the diagnosis of PJI and (2) determine whether performance of the LE strip test varied by infecting organism. This prospective study enrolled 1,015 patients undergoing hip or knee revision arthroplasty at a single institution from 2009 to September 2021. PJI was defined using a modified version of 2018 International Consensus Meeting (ICM) criteria that excluded LE when calculating the ICM score. Receiver operating characteristic curves were used to assess the utility of the LE strip test in the diagnosis of PJI. 973 patients were included in the analyses. 246 (25.4%) were classified as ICM-positive and 727 (74.6%) were classified as ICM-negative. An LE cutoff of “1+” (AUC 0.819, sensitivity 73.2%, specificity 90.6%) had superior accuracy to an LE cutoff of “2+” (AUC 0.713, sensitivity 43.9%, specificity 98.8%) in the overall diagnosis of PJI (p<0.001). When stratifying by organism type, an LE cutoff of “1+” had the best diagnostic utility for PJI caused by methicillin resistant To our knowledge, this is the largest study evaluating the utility of the LE strip test in the diagnosis of PJI. Based on our findings, it appears that a “1+” cutoff has higher diagnostic utility than a cutoff of “2+”.
A growing number of recent investigations on the human genome, gut microbiome, and proteomics suggests that the loss of mucosal barrier function, particularly in the gastrointestinal tract, may substantially affect antigen trafficking, ultimately influencing the close bidirectional interaction between the gut microbiome and the immune system. This cross-talk is highly influential in shaping the host immune system function and ultimately shifting genetic predisposition to clinical outcome. Therefore, we hypothesized that a similar interaction could affect the occurrence of acute and chronic periprosthetic joint infections (PJI). Multiple biomarkers of gut barrier disruption were tested in parallel in plasma samples collected as part of a prospective cohort study of patients undergoing revision arthroplasty for aseptic or PJI (As defined by the 2018 ICM criteria). All blood samples were collected before any antibiotic was administered. Samples were tested for Zonulin, soluble CD14 (sCD14), and lipopolysaccharide (LPS) using commercially available enzyme-linked immunosorbent assays. Statistical analysis consisted of descriptive statistics and ANOVA.Aim
Method
The efficacy of various irrigation solutions in removing microbial contamination of a surgical wound and reducing the rate of subsequent surgical site infection (SSI), has been demonstrated extensively. However, it is not known if irrigation solutions have any activity against established biofilm. This issue is pertinent as successful management of patients with periprosthetic joint infection (PJI) includes the ability to remove biofilm established on the surface of implants and necrotic tissues. The purpose of this study was to evaluate the efficacy of various irrigation solutions in eradicating established biofilm, as opposed to planktonic bacteria, in a validated Established biofilms of Aim
Method
Surgical management of PJI remains challenging with patients failing treatment despite the best efforts. An important question is whether these later failures reflect reinfection or the persistence of infection. Proponents of reinfection believe hosts are vulnerable to developing infection and new organisms emerge. The alternative hypothesis is that later failure is a result of an organism that was present in the joint but was not picked up by initial culture or was not a pathogen initially but became so under antibiotic pressure. This multicenter study explores the above dilemma. Utilizing next-generation sequencing (NGS), we hypothesize that failures after two-stage exchange arthroplasty can be caused by an organism that was present at the time of initial surgery but not isolated by culture. This prospective study involving 15 institutions collected samples from 635 revision total hip(n=310) and knee(n=325) arthroplasties. Synovial fluid, tissue and swabs were obtained intraoperatively for NGS analysis. Patients were classified per 2018 Consensus definition of PJI. Treatment failure was defined as reoperation for infection that yielded positive cultures, during minimum 1-year follow-up. Concordance of the infecting pathogen cultured at failure with NGS analysis at initial revision was determined.Aim
Method
While metagenomic (microbial DNA) sequencing technologies can detect the presence of microbes in a clinical sample, it is unknown whether this signal represents dead or live organisms. Metatranscriptomics (sequencing of RNA) offers the potential to detect transcriptionally “active” organisms within a microbial community, and map expressed genes to functional pathways of interest (e.g. antibiotic resistance). We used this approach to evaluate the utility of metatrancriptomics to diagnose PJI and predict antibiotic resistance. In this prospective study, samples were collected from 20 patients undergoing revision TJA (10 aseptic and 10 infected) and 10 primary TJA. Synovial fluid and peripheral blood samples were obtained at the time of surgery, as well as negative field controls (skin swabs, air swabs, sterile water). All samples were shipped to the laboratory for metatranscriptomic analysis. Following microbial RNA extraction and host analyte subtraction, metatranscriptomic sequencing was performed. Bioinformatic analyses were implemented prior to mapping against curated microbial sequence databases– to generate taxonomic expression profiles. Principle Coordinates Analysis (PCoA) and Partial Least Squares-Discriminant Analysis were utilized to ordinate metatranscriptomic profiles, using the 2018 definition of PJI as the gold-standard.Aim
Method
The clinical relevance of microbial DNA detected via next-generation sequencing (NGS) remains unknown. This multicenter study was conceived to: 1) identify species on NGS that may predict periprosthetic joint infection (PJI), then 2) build a predictive model for PJI in a developmental cohort, and 3) validate predictive utility of the model in a separate multi-institutional cohort. Fifteen institutions prospectively collected samples from 194 revision TKA and 184 revision THA between 2017–2019. Synovial fluid, tissue and swabs were obtained intraoperatively and sent to MicrogenDx (Lubbock, TX) for NGS analysis. Reimplantations were excluded. Patients were classified per the 2018 ICM definition of PJI. DNA analysis of community similarities (ANCOM) was used to identify 17 bacterial species of 294 (W-value>50) for differentiating infected vs. noninfected cases. Logistic regression with LASSO selection and random-forest algorithms were then used to build a model for predicting PJI. ICM classification was the response variable (gold-standard) and species identified through ANCOM were predictors. Patients were randomly allocated 1:1 into training and validation sets. Using the training set, a model for PJI diagnosis was generated. The entire model-building procedure and validation was iterated 1000 times.Aim
Method
Microbial identification in the setting of periprosthetic joint infections (PJI) is crucial to tailor the best combination of surgical and medical treatment. Given the high cost, low sensitivity and slow results associated with traditional cultures, s synovial fluid antibody assay was developed. We asked whether antibody testing may be used as a proxy to traditional culture in the setting of PJI. A retrospective study of patients who underwent revision total hip (THA) and knee (TKA) arthroplasty between January 2019 and January 2020 was performed. All patients were aspirated prior to revision surgery and antibody testing was performed. All patients had samples harvested for culture as per standard of care. Results of the two tests and their concordance when an organism was identified were compared. A frequency table was used and a McNemar test was used to compare the two methods.Aim
Method
A large body of evidence is emerging to implicate that dysregulation of the gut microbiome (dysbiosis) increases the risk of surgical site infections. Gut dysbiosis is known to occur in patients with inflammatory bowel disease (IBD), allowing for translocation of bacteria across the inflamed and highly permeable intestinal mucosal wall. The null hypothesis was that IBD was not associated with increased risk of periprosthetic joint infection (PJI) after primary total hip and knee arthroplasty. Our aim was to investigate whether a prior diagnosis of IBD was associated with a higher risk of PJI following primary total hip and knee arthroplasty. A matched cohort study was designed. Primary endpoint was the occurrence of PJI at 2-year. Secondary endpoints were aseptic revisions, as well as discharge to rehab facility, complications up to 30 days, and readmission up to 90 days after TJA. ICD-9 and −10 codes were used to identify patients with IBD and the control cohort. A chart review was performed to confirm diagnosis of IBD. Using our institutional database, 154 patients with IBD were identified and matched (3 to 1) for age, sex, body mass index (BMI), year of surgery, and joint affected with 462 individuals without IBD undergoing TJA.Aim
Method
It is traditionally stated that around 80% of all periprosthetic joint infections (PJI) are caused by well-known gram-positive organisms such as We retrospectively reviewed the medical records of 1,363 patients with confirmed PJI (559 THA and 804 TKA) who received treatment at our institution between 2000 and 2019. Pertinent data related to demographics, microbiological findings, and outcome of treatment were collected. Organisms were differentiated using culture or confirmed by Matrix-Assisted Laser Desorption Ionization-time of flight (MALDI-tof) mass spectrometry. Statistical analysis included logistic regressions.Aim
Method
D-dimer is a widely available serum test that detects fibrinolytic activities that occur during infection. Prior studies have explored its utility for diagnosis of chronic periprosthetic joint infections (PJI), but not explored its prognostic value for prediction of subsequent treatment failure. The purpose of this study was to: (1) assess the ability of serum D-dimer and other standard-of-care serum biomarkers to predict failure following reimplantation, and (2) establish a new cutoff value for serum D-dimer for prognostic use prior to reimplantation. This prospective study enrolled 92 patients undergoing reimplantation between April 2015 and March 2019 who had previously undergone total hip/knee resection arthroplasty with placement of an antibiotic spacer for treatment of chronic PJI. Serum D-dimer level, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) levels were measured preoperatively for all patients. Failure following implantation was defined per the Delphi consensus criteria. Optimal cutoffs for D-dimer, ESR, and CRP were calculated based on ROC curves and compared in their association with failure following reimplantation criteria at minimum 1-year follow-up.Aim
Method
Whether laminar airflow (LAF) in the operating room (OR) is effective for decreasing periprosthetic joint infection (PJI) following total joint arthroplasty (TJA) remains a clinically significant yet controversial issue. This study investigated the association between operating room ventilation systems and the risk of PJI in TJA patients. We performed a retrospective observational study on consecutive patients undergoing primary total knee arthroplasty (TKA) and total hip arthroplasty (THA) from January 2013-September 2017 in two surgical facilities within a single institution, with a minimum 1-year follow-up. All procedures were performed by five board-certified arthroplasty surgeons. The operating rooms at the facilities were equipped with LAF and turbulent ventilation systems, respectively. Patient characteristics were extracted from clinical records. PJI was defined according to Musculoskeletal Infection Society criteria within 1-year of the index arthroplasty. A multivariate logistic regression model was performed to explore the association between LAF and risk of 1-year PJI, and then a sensitivity analysis using propensity score matching (PSM) was performed to further validate the findings.Aim
Method
Rifampin is considered as the antibiotic corner stone in the treatment of acute staphylococcal periprosthetic joint infections (PJI). However, if, when, and how to use rifampin has been questioned. We evaluated the outcome of patients treated with and without rifampin, and analysed the influence of timing, dose and co-antibiotic. Acute staphylococcal PJIs treated with surgical debridement between 1999 and 2017, and a minimal follow-up of 1 year were evaluated. Treatment failure was defined as the need for any further surgical procedure related to infection, PJI-related death, or the need for suppressive antimicrobial treatment.Aim
Method
A growing number of recent investigations on the human genome, gut microbiome, and proteomics suggests that the loss of mucosal barrier function, particularly in the gastrointestinal tract, may substantially affect antigen trafficking, ultimately influencing the close bidirectional interaction between the gut microbiome and the immune system. This cross-talk is highly influential in shaping the host immune system and ultimately clinical infections. The hypothesis of the current study was that a change in microbiome and/or breach in GI epithelial barrier could be partially responsible for development of periprosthetic joint infections (PJI). Multiple biomarkers of gut barrier disruption were tested in parallel in plasma samples collected as part of a prospective cohort study of patients undergoing revision arthroplasty for aseptic failures or PJI (As defined by the 2018 ICM criteria). All blood samples were collected before any antibiotic was administered. Samples were tested for Zonulin, soluble CD14 (sCD14), and lipopolysaccharide (LPS) using commercially available enzyme-linked immunosorbent assays. Statistical analysis consisted of descriptive statistics, Mann-Whitney t-test, and Kruskal-Wallis test. A total of 134 patients were consented and included in the study. 44 were classified as PJI (30 chronic and 14 acute), and 90 as aseptic failures (26 primaries and 64 aseptic revisions). Both Zonulin and sCD14, but not LPS, were found to be significantly increased in the PJI group compared to non-infected cases (p<0.001; p=0.003). Higher levels of Zonulin were found in acute infections compared to chronic PJI (p=0.005 This prospective ongoing study reveals a possible link between gut permeability and the ‘gut-immune-joint axis’ in PJI. If this association continues to be born out with larger cohort recruitment and more in-depth analysis, it would have an immense implication in managing patients with PJI. In addition to administering antimicrobials, patients with PJI and other orthopedic infections may require gastrointestinal modulators such as pro and prebiotics.
The optimal management of an infrapopliteal deep venous thrombosis (IDVT) following total knee arthroplasty (TKA) remains unknown. The risk of DVT propagation and symptom progression must be balanced against potential haemorrhagic complications associated with administration of anticoagulation therapy. The current study reports on a cohort of patients diagnosed with IDVT following TKA who were treated with aspirin, followed closely for development of symptoms, and scanned with ultrasound to determine resolution of IDVT. Among a cohort of 5,078 patients undergoing TKA, 532 patients (695 TKAs, 12.6%) developed an IDVT between 1 January 2014 to 31 December 2019 at a single institution, as diagnosed using Doppler ultrasound at the first postoperative visit. Of the entire cohort of 532 patients with IDVT, 91.4% (486/532) were treated with aspirin (325 mg twice daily) and followed closely. Repeat lower limb ultrasound was performed four weeks later to evaluate the status of IDVT.Aims
Methods
Surgical management of PJI remains challenging with patients failing treatment despite the best efforts. An important question is whether these later failures reflect reinfection or the persistence of infection. Proponents of reinfection believe hosts are vulnerable to developing infection and new organisms emerge. The alternative hypothesis is that later failure is a result of an organism that was present in the joint but was not picked up by initial culture or was not a pathogen initially but became so under antibiotic pressure. This multicenter study explores the above dilemma. Utilizing next-generation sequencing (NGS), we hypothesize that failures after two stage exchange arthroplasty can be caused by an organism that was present at the time of initial surgery but not isolated by culture. This prospective study involving 15 institutions collected samples from 635 revision total hip (n=310) and knee (n=325) arthroplasties. Synovial fluid, tissue and swabs were obtained intraoperatively for NGS analysis. Patients were classified per 2018 Consensus definition of PJI. Treatment failure was defined as reoperation for infection that yielded positive cultures, during minimum 1-year follow-up. Concordance of the infecting pathogen cultured at failure with NGS analysis at initial revision was determined.Introduction
Methods
Failure of irrigation and debridement (I&D) for prosthetic joint infection (PJI) is influenced by numerous host, surgical, and pathogen-related factors. We aimed to develop and validate a practical, easy-to-use tool based on machine learning that may accurately predict outcome following I&D surgery taking into account the influence of numerous factors. This was an international, multicentre retrospective study of 1,174 revision total hip (THA) and knee arthroplasties (TKA) undergoing I&D for PJI between January 2005 and December 2017. PJI was defined using the Musculoskeletal Infection Society (MSIS) criteria. A total of 52 variables including demographics, comorbidities, and clinical and laboratory findings were evaluated using random forest machine learning analysis. The algorithm was then verified through cross-validation.Aims
Methods
The aim of this study was to determine if a three-month course of microorganism-directed oral antibiotics reduces the rate of failure due to further infection following two-stage revision for chronic prosthetic joint infection (PJI) of the hip and knee. A total of 185 patients undergoing a two-stage revision in seven different centres were prospectively enrolled. Of these patients, 93 were randomized to receive microorganism-directed oral antibiotics for three months following reimplantation; 88 were randomized to receive no antibiotics, and four were withdrawn before randomization. Of the 181 randomized patients, 28 were lost to follow-up, six died before two years follow-up, and five with culture negative infections were excluded. The remaining 142 patients were followed for a mean of 3.3 years (2.0 to 7.6) with failure due to a further infection as the primary endpoint. Patients who were treated with antibiotics were also assessed for their adherence to the medication regime and for side effects to antibiotics.Aims
Methods
Treatment success of debridement, antibiotics and implant retention (DAIR) is in early periprosthetic joint infection (PJI) is largely dependent on the presence or absence of a mature biofilm. In what time interval a mature biofilm develops is still unclear, and therefore, the time point at which DAIR should be disrecommended remains to be established. This large multicenter trial evaluated the failure rates of DAIR for different time intervals from index arthroplasty to DAIR in early PJI. We retrospectively evaluated patients with early PJI treated with DAIR between 1996 and 2016. Early PJI was defined as a PJI that developed within 90 days after index arthroplasty. Patients with hematogenous infections, arthroscopic debridements and a follow-up less than one year were excluded. Treatment failure was defined as 1) any further surgical procedure related to infection 2) PJI-related death, or 3) long-term suppressive antibiotics, all within one year after DAIR.Aim
Method
The purpose of this multi-center, randomized clinical trial was to compare static and articulating spacers in the treatment of PJI complicating total knee arthroplasty TKA. 68 Patients treated with two-stage exchange arthroplasty were randomized to either a static (32 patients) or an articulating (36 patients) spacer. A power analysis determined that 28 patients per group were necessary to detect a 13º difference in range of motion between groups. Six patients were excluded after randomization, six died, and seven were lost to follow-up prior to two years.Background
Methods
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. 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.Introduction
Methods
