A decision analysis of treatment strategies for acute periprosthetic joint infection: Early irrigation and debridement versus delayed treatment based on organism

Timing-specific Debridement, Antibiotics, and Implant Retention and 2-Stage Revision for Megaprosthesis-Related Infection: Optimizing the Window Period for Improved Outcomes

Background

This study aimed to evaluate the outcomes of debridement, antibiotics, and implant retention (DAIR) procedures and 2-stage revision surgeries in patients with periprosthetic joint infection following megaprosthesis, including treatment failure; the patient-reported outcomes; and to determine the survival rates of the revised megaprosthesis.

Methods

A retrospective study of 30 patients diagnosed with periprosthetic joint infection following megaprosthesis between 2018 and 2023, with minimum 1-year follow-up. Patients with previous unsuccessful debridement in other institutions were excluded. Patients presenting within 4 weeks of megaprosthesis implantation underwent the DAIR procedure, while those presenting after this window were taken for a 2-stage revision surgery. The primary outcome was treatment failure, defined as persistent wound complication or the need for subsequent surgical intervention. The secondary outcomes included patient-reported outcomes, assessed with the Oxford Hip Score and Oxford Knee Score, and the survival rates of the revised megaprosthesis.

Results

The mean follow-up duration for all patients was 38 ± 12.6 months. Improvement was found for Oxford Hip Score and Oxford Knee Score with mean 34.22 ± 9.2 and 32.40 ± 8.1, respectively, at the 1-year follow-up. DAIR achieved an 81% success rate (13 out of 16) and 2-stage exchange had a 71.4% success rate (10 out of 14).

Conclusions

Both DAIR and 2-stage exchange procedures yielded favorable functional outcomes with satisfactory 2-year survival function. Careful patient selection and indication management are crucial for optimal results.

Level of evidence

Level IV.

Bibliometric Analysis of Outpatient Hip and Knee Arthroplasty Research Evolution

Objectives

Total joint arthroplasty is an effective treatment for end stage osteoarthritis. As perioperative protocols are developed, outpatient arthroplasty has been gaining traction to facilitate earlier recovery and same day discharge. The aim of this manuscript is to analyze the trends in outpatient arthroplasty over a 17-year duration. This analysis seeks to predict emerging themes in the literature on patient optimization and outcomes in outpatient arthroplasty.

Methods

This study conducted a literature review on outpatient arthroplasty with the Web of Science Core Collection over a 17-year period between 2005 and 2022. Bibliometric data was imported and analyzed with Bibliometrix and VOSviewer.

Results

198 articles were identified demonstrating an annual growth of 19.61% with notable bursts in 2017 and 2021. United States was the top global contributor followed by Canada and European nations. There were significant contributions across 219 institutions and 758 authors, with the Journal of Arthroplasty being the most productive and influential journals. Key themes identified include the feasibility of outpatient surgery, pain management, and perioperative complications and costs.

Conclusion

This bibliometric analysis highlights the ongoing growth and development within outpatient arthroplasty since 2005. The United States remain the global leader within outpatient related arthroplasty research. Previous, current, and ongoing trends are highlighted within this field for further development as hotspots.

The presence of a sinus tract is associated with reinfection after two-stage revision surgery for prosthetic hip joint infection: a case-control study

BACKGROUND

Reinfection rates after two-stage revision (TSR) for prosthetic joint infection (PJI) range from 7.9 to 14%. Many factors, including sinus tracts, are associated with reinfection after this procedure. This study aimed to delineate whether the presence of sinus tract could increase reinfection rate after TSR and to investigate other potential risk factors for reinfection after TSR.

METHODS

We conducted a case-control study by retrospectively reviewing patients who underwent TSR for prosthetic hip joint infection from 2002 to 2022. The case group included patients who developed reinfection after TSR, while the control group consisted of patients who did not experience reinfection. PJI and reinfection after TSR were defined based on Delphi-based international consensus criteria. Patient demographics, past medical history, clinical manifestations, laboratory results, interval between stages, microbiological culture results were collected. Univariate analyses were utilized to assess the effect of sinus tract on reinfection and to identify other risk factors for reinfection after TSR.

RESULTS

Six patients with reinfection after TSR were included as the case group and 32 patients without reinfection were in the control group. Significant difference was observed in percentage of patients with sinus tracts between the two groups (67% in the case group versus 19% in the control group, p = 0.031, OR = 8.7). Significant difference was also found in percentage of patients with positive cultures of synovial fluid and synovium harvested during the first-stage revision between the two groups (100% in the case group versus 50% in the control group, p = 0.030). Additionally, patients in the case group had a significantly higher C-reactive protein (CRP) level prior to the second stage revision than that of patients in the control group (8.80 mg/L versus 2.36 mg/L, p = 0.005), despite normal CRP levels in all patients.

CONCLUSIONS

Our study revealed that the presence of sinus tracts could significantly increase risk of postoperative reinfection after TSR. Positive cultures during the first stage revision and elevated CRP level prior to the second stage revision could also increase the risk of reinfection after TSR. Further studies with a larger sample size are required.

TRIAL REGISTRATION

Retrospectively registered.

The Complicated Case of Staphylococcus aureus Bacteremia Associated With Delayed-Onset Prosthetic Joint Infection: A Case Report and Review of Management Strategies

Staphylococcus aureus (S. aureus), an opportunistic Gram-positive bacterium, is notorious for causing a plethora of clinical diseases. While it does not typically infect healthy skin, S. aureus infections are prevalent in both community-acquired and hospital-acquired settings. Rheumatoid arthritis (RA), a chronic autoimmune disease characterized by joint inflammation and progressive bone erosion, can be managed medically and, in moderate to severe cases, surgically through arthroplasty. Complications of arthroplasty include wound infection, blood clots, stiffness, and infection around the prosthesis. Prosthetic joint infections (PJIs) are a rare complication of arthroplasty, commonly caused by aerobic Gram-positive bacteria. These infections can lead to bacteremia, precipitating a cascade of adverse clinical sequelae. This report aims to explore the etiology of delayed-onset PJIs, the underlying pathophysiology of this condition leading to bacteremia, the complications of S. aureus bacteremia, and the management strategies employed to treat PJIs and complicated cases of S. aureus bacteremia resulting from PJIs.

Achieving High Accuracy in Predicting the Probability of Periprosthetic Joint Infection From Synovial Fluid in Patients Undergoing Hip or Knee Arthroplasty: The Development and Validation of a Multivariable Machine Learning Algorithm

Background and objective The current periprosthetic joint infection (PJI) diagnostic guidelines require clinicians to interpret and integrate multiple criteria into a complex scoring system. Also, PJI classifications are often inconclusive, failing to provide a clinical diagnosis. Machine learning (ML) models could be leveraged to reduce reliance on these complex systems and thereby reduce diagnostic uncertainty. This study aimed to develop an ML algorithm using synovial fluid (SF) test results to establish a PJI probability score. Methods We used a large clinical laboratory's dataset of SF samples, aspirated from patients with hip or knee arthroplasty as part of a PJI evaluation. Patient age and SF biomarkers [white blood cell count, neutrophil percentage (%PMN), red blood cell count, absorbance at 280 nm wavelength, C-reactive protein (CRP), alpha-defensin (AD), neutrophil elastase, and microbial antigen (MID) tests] were used for model development. Data preprocessing, principal component analysis, and unsupervised clustering (K-means) revealed four clusters of samples that naturally aggregated based on biomarker results. Analysis of the characteristics of each of these four clusters revealed three clusters (n=13,133) with samples having biomarker results typical of a PJI-negative classification and one cluster (n=4,032) with samples having biomarker results typical of a PJI-positive classification. A decision tree model, trained and tested independently of external diagnostic rules, was then developed to match the classification determined by the unsupervised clustering. The performance of the model was assessed versus a modified 2018 International Consensus Meeting (ICM) criteria, in both the test cohort and an independent unlabeled validation set of 5,601 samples. The SHAP (SHapley Additive exPlanations) method was used to explore feature importance. Results The ML model showed an area under the curve of 0.993, with a sensitivity of 98.8%, specificity of 97.3%, positive predictive value (PPV) of 92.9%, and negative predictive value (NPV) of 99.8% in predicting the modified 2018 ICM diagnosis among test set samples. The model maintained its diagnostic accuracy in the validation cohort, yielding 99.1% sensitivity, 97.1% specificity, 91.9% PPV, and 99.9% NPV. The model's inconclusive rate (diagnostic probability between 20-80%) in the validation cohort was only 1.3%, lower than that observed with the modified 2018 ICM PJI classification (7.4%; p<0.001). The SHAP analysis found that AD was the most important feature in the model, exhibiting dominance among >95% of "infected" and "not infected" diagnoses. Other important features were the sum of the MID test panel, %PMN, and SF-CRP. Conclusions Although defined methods and tools for diagnosis of PJI using multiple biomarker criteria are available, they are not consistently applied or widely implemented. There is a need for algorithmic interpretation of these biomarkers to enable consistent interpretation of the results to drive treatment decisions. The new model, using clinical parameters measured from a patient's SF sample, renders a preoperative probability score for PJI which performs well compared to a modified 2018 ICM definition. Taken together with other clinical signs, this model has the potential to increase the accuracy of clinical evaluations and reduce the rate of inconclusive classification, thereby enabling more appropriate and expedited downstream treatment decisions.

Diagnosis and management of infected arthroplasty

Periprosthetic joint infection (PJI) is one of the most dreadful complications after THA and TKA. Though prevention is of utmost importance in PJI management, the last decade has seen many remarkable developments in PJI diagnosis, including the introduction of several standardized PJI diagnostic definitions and biomarkers. Depending on the specific clinical situation, a myriad of treatment options for PJI are offered. Our review aims to summarize the pertinent information on PJI diagnosis and synthesize literature on the different treatment methods currently used in clinical practice. One of the most accepted PJI diagnostic definitions was developed by the Musculoskeletal Infection Society (MSIS) in 2011, later modified in the 2013 International Consensus Meeting (ICM). After promising results from studies, alpha-defensins and D-dimer were recently incorporated into the 2018 ICM PJI definition. The management choices for PJI include irrigation and debridement (DAIR), one-stage exchange arthroplasty, or two-stage exchange arthroplasty, to name a few. While two-stage revision has traditionally been the treatment of choice in the United States, there has been a growing body of evidence framing one-stage revision as a comparable choice. One-stage revision should be offered in patients meeting strict selection criteria: no sinus tract, proper soft tissue available for wound closure, appropriate bone stock, a favorable identifiable organism with encouraging antibiotic sensitivities (for cement and oral suppression later), and robust immunological status. DAIR can be considered in case of early infections with sensitive infecting organisms. Patients with multiple unsuccessful revisions or those who refuse further surgical intervention for PJI can be offered antibiotic suppression. If nothing seems to work, salvage procedures (resection arthroplasty and arthrodesis) are available as a last resort. Further research is encouraged to improve on diagnostic capabilities and develop evidence on the best treatment of choice for PJI.

The role of fibrinogen in predicting reinfection after DAIR for periprosthetic joint infections

Background

Fibrinogen (FIB) has been found to be a promising marker in diagnosing periprosthetic joint infection (PJI), however, the value of FIB in predicting reinfection of PJI is unknown. The purpose of this study was to evaluate the value of FIB in predicting reinfection after debridement, antibiotics, and implant retention (DAIR) for PJI.

Methods

We retrospectively analyzed the clinical data of patients who were diagnosed with PJI and underwent DAIR from 2013 to 2019. The levels of the FIB, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) were measured before DAIR. After DAIR, patients were followed and reinfections were identified. For both acute and chronic PJI, the predictive value of FIB was evaluated by calculating the sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic curve (ROC), and was compared with traditional inflammatory markers including ESR and CRP.

Results

The expression of FIB differed between patients reinfected and those not reinfected in both acute and chronic PJI (p < 0.05). In patients who underwent DAIR for acute PJI, the sensitivity and specificity of FIB were 81.82 and 83.33%, respectively, which were significantly higher than that of CRP (sensitivity, 72.73%; specificity, 50%; p < 0.05), while the specificity was higher than that of ESR (specificity, 41.67%; p < 0.05). In patients who underwent DAIR for chronic PJI, the sensitivity and specificity of FIB were 80.00 and 66.66%, respectively, which were significantly higher than that of CRP (sensitivity, 53.33%; specificity, 66.66%; p < 0.05) and ESR (sensitivity was 66.00%; specificity, 16.66%; p < 0.05). The ROC curves showed that FIB demonstrated the highest AUC among the biomarkers in both acute and chronic PJI.

Conclusion

FIB is a promising indicator in predicting reinfection after DAIR for both acute and chronic PJI, and it seems to perform better than ESR and CRP.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04357-8.