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
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
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
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
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
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
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
The best marker for assessing glycaemic control prior to total knee arthroplasty (TKA) remains unknown. The purpose of this study was to assess the utility of fructosamine compared with glycated haemoglobin (HbA1c) in predicting early complications following TKA, and to determine the threshold above which the risk of complications increased markedly. This prospective multi-institutional study evaluated primary TKA patients from four academic institutions. Patients (both diabetics and non-diabetics) were assessed using fructosamine and HbA1c levels within 30 days of surgery. Complications were assessed for 12 weeks from surgery and included prosthetic joint infection (PJI), wound complication, re-admission, re-operation, and death. The Youden’s index was used to determine the cut-off for fructosamine and HbA1c associated with complications. Two additional cut-offs for HbA1c were examined: 7% and 7.5% and compared with fructosamine as a predictor for complications.Aims
Patients and Methods
Despite recent advances in the diagnosis of periprosthetic joint infection(PJI), identifying the infecting organism continues to be a challenge, with up to a third of PJIs reported to have negative cultures. Current molecular techniques have thus far been unable to replace culture as the gold standard for isolation of the infecting pathogen. Next- generation sequencing(NGS) is a well-established technique for comprehensively sequencing the entire pathogen DNA in a given sample and has recently gained much attention in many fields of medicine. Our aim was to evaluate the ability of NGS in identifying the causative organism(s) in patients with PJI. After obtaining Institutional Review Board approval and informed consent for all study participants, samples were prospectively collected from 148 revision total joint arthroplasty procedures (83 knees, 65 hips). Synovial fluid, deep tissue and swabs were obtained at the time of surgery and shipped to the laboratory for NGS analysis (MicroGenDx). Deep tissue specimens were also sent to the institutional laboratory(Thomas Jefferson University Hospital) for culture. PJI was diagnosed using the Musculoskeletal Infection Society(MSIS) definition of PJI. Statistical analysis was performed using SPSS software.Introduction
Methods
The use of irrigation solution during surgical procedures is a common and effective practice in reduction of bioburden and the risk of subsequent infection. The optimal irrigation solution to accomplish this feat remains unknown. Many surgeons commonly add topical antibiotics to irrigation solutions assuming this has topical effect and eliminates bacteria. The latter reasoning has never been proven. In fact a few prior studies suggest addition of antibiotics to irrigation solution confers no added benefit. Furthermore, this practice adds to cost, has the potential for anaphylactic reactions, and may also contribute to the emergence of antimicrobial resistance. We therefore sought to compare the antimicrobial efficacy and cytotoxicity of irrigation solution containing polymyxin-bacitracin versus other commonly used irrigation solutions. Using two Cytotoxicity analysis in human fibroblast, osteoblast, and chrondrocyte cells exposed to each of the respective irrigation solutions was performed by visualization of cell structure, lactate dehydrogenase (LDH) activity and evaluation of vital cells. Toxicity was quantified by determination of LDH release (ELISA % absorbance; with higher percentage considered a surrogate for cytotoxicity). Descriptive statistics were used to present means and standard deviation of triplicate experimental runs.Introduction
Methods
Recent reports demonstrate that Next Generation Sequencing (NGS) facilitates pathogen identification in the context of culture-negative PJI; however the clinical relevance of the polymicrobial genomic signal often generated remains unknown. This study was conceived to explore: (1) the ability of NGS to identify pathogens in culture-negative PJI; and (2) determine whether organisms detected by NGS, as part of a prospective observational study, had any role in later failure of patients undergoing surgical treatment for PJI. In this prospective study samples were collected in 238 consecutive patients undergoing revision total hip and knee arthroplasties. Of these 83 patients (34.9%) had PJI, as determined using the Musculoskeletal Infection Society (MSIS) criteria, and of these 20 were culture-negative (CN-PJI). Synovial fluid, deep tissue and swabs were obtained at the time of surgery and sent for NGS and culture/MALDI-TOF. Patients undergoing reimplantation were excluded. Treatment failure was assessed using the previously described Delphi criteria. In cases of re-operation, organisms present were confirmed by culture and MALDI-TOF. Concordance of the infecting pathogen(s) at failure with the NGS analysis at the initial stage CN- PJI procedure was determined.Background
Methods
The aim of this study was to examine the association between
postoperative glycaemic variability and adverse outcomes following
orthopaedic surgery. This retrospective study analyzed data on 12 978 patients (1361
with two operations) who underwent orthopaedic surgery at a single
institution between 2001 and 2017. Patients with a minimum of either
two postoperative measurements of blood glucose levels per day,
or more than three measurements overall, were included in the study.
Glycaemic variability was assessed using a coefficient of variation
(CV). The length of stay (LOS), in-hospital complications, and 90-day
readmission and mortality rates were examined. Data were analyzed
with linear and generalized linear mixed models for linear and binary
outcomes, adjusting for various covariates.Aims
Patients and Methods
The diagnosis of periprosthetic joint infection can be difficult
due to the high rate of culture-negative infections. The aim of
this study was to assess the use of next-generation sequencing for
detecting organisms in synovial fluid. In this prospective, single-blinded study, 86 anonymized samples
of synovial fluid were obtained from patients undergoing aspiration
of the hip or knee as part of the investigation of a periprosthetic
infection. A panel of synovial fluid tests, including levels of
C-reactive protein, human neutrophil elastase, total neutrophil
count, alpha-defensin, and culture were performed prior to next-generation
sequencing.Aims
Materials and Methods
Next-generation sequencing (NGS) is a well-established technique for amplification and sequencing of DNA and has recently gained much attention in many fields of medicine. Our aim was to evaluate the ability of NGS in identifying the causative organism(s) in patients with periprosthetic joint infection (PJI). In this prospective study samples were collected from 78 revision total hip arthroplasties. Synovial fluid, deep tissue and swabs were obtained at the time of surgery and shipped to the laboratory for NGS analysis. Deep tissue specimens were also sent to the institutional lab for culture. PJI was diagnosed using the Musculoskeletal infection society (MSIS) definition of PJI. Thirty-four revisions were considered infected; culture was positive in 25 of these (25/34, 73.5%), while NGS was positive in 26 (26/34, 76.4%). Among the positive cultures, complete concordance between NGS and culture in 21 cases (21/25, 84.0%). 4 cases were discordant. Among these cases, 3 cases were culture-positive and NGS-negative, while 1 was both positive on NGS and culture for disparate organisms. Among the 9 cases of culture-negative PJI(CN-PJI), NGS was able to identify an organism in 4 cases (4/9, 44.4%). The remaining 5 cases were negative on both NGS and culture (5/9, 55.6%). Forty-four revisions were considered to be aseptic; NGS exclusively identified microbes in 7 of 44 “aseptic” revisions (15.9%) and culture exclusively isolated an organism in 3 of 44 cases (6.8%). Both NGS and culture were positive in 1 of case however the result was discordant. The remaining cases (33/44, 75.0%) were both NGS and culture negative. NGS detected several organisms in most positive samples, with a greater number of organisms detected in aseptic compared to septic cases (7 vs. 3.7, respectively). NGS may be a promising technique for identifying the infecting organism in PJI. Our findings suggest that some cases of PJI may be polymicrobial that escape detection using conventional culture.
