Differences between infected and noninfected synovial fluid

Synovial fluid NMR-based metabolomics in septic and aseptic revision total knee arthroplasty: Implications on diagnosis and treatment

Periprosthetic joint infection (PJI) is one of the most challenging complications following total knee arthroplasty. Despite its importance, there is a paucity of reports in the literature regarding its pathogenesis. Recently, cellular metabolic reprogramming has been shown to play an important role in the progression and outcome of infectious diseases. Therefore, the aim of this study was to evaluate the metabolites composition of the synovial fluid from patients with PJI or aseptic failure of total knee arthroplasties. The synovial fluids from 21 patients scheduled for revision total knee arthroplasty (11 with the diagnosis of PJI and 10 with aseptic failures) were analyzed using 1D 1H NMR spectroscopy. Univariate and multivariate statistical analyzes were used to identify metabolites that were differentially abundant between those groups. A total of 28 metabolites were identified and five of them found to be differentially abundant between infected and non-infected synovial fluids. Lactate, acetate and 3-hydroxybutyrate were found to be in a higher concentration, and glucose and creatine were found reduced in the synovial fluid from PJI patients. Synovial fluid from patients with PJI exhibit a distinct metabolic profile, possibly reflecting metabolic adaptation that occurs in the infected periprosthetic microenvironment. Further research and studies are warranted to gain a broader insight into the metabolic pathways engaged by both pathogen and immune cells in the context of a PJI.

Diagnosis of periprosthetic joint infections in patients who have rheumatoid arthritis

Aims

To investigate the optimal thresholds and diagnostic efficacy of commonly used serological and synovial fluid detection indexes for diagnosing periprosthetic joint infection (PJI) in patients who have rheumatoid arthritis (RA).

Methods

The data from 348 patients who had RA or osteoarthritis (OA) and had previously undergone a total knee (TKA) and/or a total hip arthroplasty (THA) (including RA-PJI: 60 cases, RA-non-PJI: 80 cases; OA-PJI: 104 cases, OA-non-PJI: 104 cases) were retrospectively analyzed. A receiver operating characteristic curve was used to determine the optimal thresholds of the CRP, ESR, synovial fluid white blood cell count (WBC), and polymorphonuclear neutrophil percentage (PMN%) for diagnosing RA-PJI and OA-PJI. The diagnostic efficacy was evaluated by comparing the area under the curve (AUC) of each index and applying the results of the combined index diagnostic test.

Results

For PJI prediction, the results of serological and synovial fluid indexes were different between the RA-PJI and OA-PJI groups. The optimal cutoff value of CRP for diagnosing RA-PJI was 12.5 mg/l, ESR was 39 mm/hour, synovial fluid WBC was 3,654/μl, and PMN% was 65.9%; and those of OA-PJI were 8.2 mg/l, 31 mm/hour, 2,673/μl, and 62.0%, respectively. In the RA-PJI group, the specificity (94.4%), positive predictive value (97.1%), and AUC (0.916) of synovial fluid WBC were higher than those of the other indexes. The optimal cutoff values of synovial fluid WBC and PMN% for diagnosing RA-PJI after THA were significantly higher than those of TKA. The specificity and positive predictive value of the combined index were 100%.

Conclusion

Serum inflammatory and synovial fluid indexes can be used for diagnosing RA-PJI, for which synovial fluid WBC is the best detection index. Combining multiple detection indexes can provide a reference basis for the early and accurate diagnosis of RA-PJI.

Characterization of periprosthetic environment microbiome in patients after total joint arthroplasty and its potential correlation with inflammation

AIMS

Periprosthetic joint infection (PJI) is one of the most serious complications after total joint arthroplasty (TJA) but the characterization of the periprosthetic environment microbiome after TJA remains unknown. Here, we performed a prospective study based on metagenomic next-generation sequencing to explore the periprosthetic microbiota in patients with suspected PJI.

METHODS

We recruited 28 patients with culture-positive PJI, 14 patients with culture-negative PJI, and 35 patients without PJI, which was followed by joint aspiration, untargeted metagenomic next-generation sequencing (mNGS), and bioinformatics analysis. Our results showed that the periprosthetic environment microbiome was significantly different between the PJI group and the non-PJI group. Then, we built a "typing system" for the periprosthetic microbiota based on the RandomForest Model. After that, the 'typing system' was verified externally.

RESULTS

We found the periprosthetic microbiota can be classified into four types generally: "Staphylococcus type," "Pseudomonas type," "Escherichia type," and "Cutibacterium type." Importantly, these four types of microbiotas had different clinical signatures, and the patients with the former two microbiota types showed obvious inflammatory responses compared to the latter ones. Based on the 2014 Musculoskeletal Infection Society (MSIS) criteria, clinical PJI was more likely to be confirmed when the former two types were encountered. In addition, the Staphylococcus spp. with compositional changes were correlated with C-reactive protein levels, the erythrocyte sedimentation rate, and the synovial fluid white blood cell count and granulocyte percentage.

CONCLUSIONS

Our study shed light on the characterization of the periprosthetic environment microbiome in patients after TJA. Based on the RandomForest model, we established a basic "typing system" for the microbiota in the periprosthetic environment. This work can provide a reference for future studies about the characterization of periprosthetic microbiota in periprosthetic joint infection patients.

Application of 68Ga-citrate PET/CT for differentiating periprosthetic joint infection from aseptic loosening after joint replacement surgery

AIMS

We aimed to evaluate the utility of ⁶⁸Ga-citrate positron emission tomography (PET)/CT in the differentiation of periprosthetic joint infection (PJI) and aseptic loosening (AL), and compare it with ^99mTc-methylene bisphosphonates (^99mTc-MDP) bone scan.

METHODS

We studied 39 patients with suspected PJI or AL. These patients underwent ⁶⁸Ga-citrate PET/CT, ^99mTc-MDP three-phase bone scan and single-photon emission CT (SPECT)/CT. PET/CT was performed at ten minutes and 60 minutes after injection, respectively. Images were evaluated by three nuclear medicine doctors based on: 1) visual analysis of the three methods based on tracer uptake model, and PET images attenuation-corrected with CT and those not attenuation-corrected with CT were analyzed, respectively; and 2) semi-quantitative analysis of PET/CT: maximum standardized uptake value (SUVmax) of lesions, SUVmax of the lesion/SUVmean of the normal bone, and SUVmax of the lesion/SUVmean of the normal muscle. The final diagnosis was based on the clinical and intraoperative findings, and histopathological and microbiological examinations.

RESULTS

Overall, 23 and 16 patients were diagnosed with PJI and AL, respectively. The sensitivity and specificity of three-phase bone scan and SPECT/CT were 100% and 62.5%, 82.6%, and 100%, respectively. Attenuation correction (AC) at 60 minutes and non-AC at 60 minutes of PET/CT had the same highest sensitivity and specificity (91.3% and 100%), and AC at 60 minutes combined with SPECT/CT could improve the diagnostic efficiency (sensitivity = 95.7%). Diagnostic efficacy of the SUVmax was low (area under the curve (AUC) of ten minutes and 60 minutes was 0.814 and 0.806, respectively), and SUVmax of the lesion/SUVmean of the normal bone at 60 minutes was the best semi-quantitative parameter (AUC = 0.969).

CONCLUSION

⁶⁸Ga-citrate showed the potential to differentiate PJI from AL, and visual analysis based on uptake pattern of tracer was reliable. The visual analysis method of AC at 60 minutes, combined with ^99mTc-MDP SPECT/CT, could improve the sensitivity from 91.3% to 95.7%. In addition, a major limitation of our study was that it had a limited sample size, and more detailed studies with a larger sample size are warranted. Cite this article: Bone Joint Res 2022;11(6):398-408.