Novel diagnostic markers for periprosthetic joint infection: a systematic review

Fracture-related infection blood-based biomarkers: Diagnostic strategies

Fracture-related infections are significant postoperative complications that carry substantial patient burden and additional healthcare costs. Despite their impact on outcome, early diagnosis of these infections remains challenging due to current available tests lacking acceptable diagnostic parameters. This review compiles existing information on blood-based biomarkers that have been evaluated as early diagnostic tools and highlights the challenges in their reliability. To begin to overcome these challenges new avenues of biomarker discovery utilizing "omics" technologies and novel analytical methods are being investigated in recent years. It appears that, despite their complexity, these newer approaches may be the future in biomarker discovery for fracture-related infection diagnosis.

Feasibility of mNGS in joint replacement patients exhibiting elevated ESR and CRP levels without an underlying diagnosis

OBJECTIVE

The aim of this study is to investigate the viability of performing initial artificial joint replacement surgery in patients presenting with unexplained elevations in erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) levels.

METHODS

A cohort of 22 patients, comprising 11 cases each for knee and hip joint replacements, who underwent initial artificial joint replacement surgery between November 2020 and January 2022, was recruited. All patients exhibited elevated levels of ESR and CRP prior to surgery, the etiology of which remained undetermined. Intraoperatively, joint effusion and periarticular tissues were preserved for subsequent bacterial culture and metagenomic next-generation sequencing (mNGS). Postoperatively, a combination of intravenous and local antibiotics was administered for anti-infective management. In cases where bacterial culture and/or mNGS yielded positive results, patients were diagnosed with periprosthetic joint infections (PJI) and underwent one-stage revision; conversely, negative findings led to the discontinuation of intravenous and local antibiotics therapy.

RESULTS

Among the cohort of 22 patients, bacterial cultures yielded negative results, while mNGS identified bacterial infection in 14 patients (63.63%), viral infection in 1 patient (4.55%), and yielded negative results in 7 patients (31.82%). All surgical incisions achieved per primam. Subsequent follow-up assessments conducted for more than 1 year postoperatively revealed absence of PJI among the patients, all of whom exhibited satisfactory progress in their rehabilitation exercises. Notably, the Knee Society Score (KSS) for knee joint patients significantly improved from a preoperative mean of 48.7 ± 3.3 points to 84.3 ± 2.2 points postoperatively, whereas the Harris Hip Score for hip joint patients increased significantly from preoperative mean of 50.6 ± 3.6 points to 87.1 ± 1.6 points (P < 0.01).

CONCLUSION

In cases where patients present with unexplained elevations in ESR and CRP levels, primary artificial joint replacement can be undertaken following a one-stage revision approach for PJI.

Construction and evaluation of a combined diagnostic model for chronic periprosthetic joint infection based on serological tests

BACKGROUND

Early diagnosis of chronic periprosthetic joint infection (CPJI) is crucial for ensuring effective treatment and improving patient outcomes. However, many auxiliary diagnostic tests are challenging to implement on a large scale due to economic and technical constraints, making CPJI diagnosis difficult. This study aims to design and validate a combined diagnostic model based on commonly used serological tests to evaluate its diagnostic value for CPJI and develop a diagnostic nomogram.

METHODS

A retrospective study from January 2019 to February 2024 involving 170 patients undergoing knee and hip arthroplasty revision for CPJI and aseptic loosening (AL) was conducted across two medical centers. These patients were divided into the training set and validation set. Patients were categorized into CPJI and AL groups based on infection status. Serological tests conducted upon admission were collected, and single-factor and multi-factor logistic regression analyses were used to identify independent diagnostic factors for early infection. These factors were integrated to construct a nomogram model. The model's performance was evaluated using the receiver operating characteristic area under the curve (AUC), Hosmer-Lemeshow test, decision curve analysis (DCA), and calibration curve, with external validation conducted on the validation set.

RESULTS

Multivariate logistic regression analysis showed that C-reactive protein (CRP), procalcitonin (PCT), and Platelet count/mean platelet volume ratio (PVR) were independent diagnostic factors for CPJI (p < 0.05). The AUCs for diagnosing CPJI using these individual factors were 0.806, 0.616, and 0.700 (p < 0.05), respectively, while their combined detection achieved an AUC of 0.861 (p < 0.05). The DCA clinical impact curve shows the combined model has good clinical utility when the threshold probability of infection presence is between 0.16 and 0.95. Similar results were obtained in the external validation cohort, with the combined detection having an AUC of 0.893.

CONCLUSION

The combined diagnostic model of CRP, PCT, and PVR significantly improves the The combined diagnostic model of CRP, PCT, and PVR significantly improves the diagnostic performance for CPJI compared to individual serum biomarkers. It exhibits good sensitivity, specificity, and clinical applicability, providing valuable references for CPJI diagnosis.

Active myeloperoxidase: a promising biomarker to differentiate "acute" and "low-grade" peri-prosthetic joint infections from aseptic failures

Introduction

The accurate distinction between periprosthetic joint infections (PJI) and aseptic failures (AF) is of paramount importance due to differences in treatment. However, this could be challenging by using the current criteria. Various synovial fluid biomarkers are being assessed to improve the diagnostic accuracy. Myeloperoxidase (MPO), an enzyme contained in the granules of neutrophils, may be a promising biomarker for PJI.

Methods

Synovial fluids of 99 patients (n = 65 PJI according to EBJIS criteria; n = 34 AF) were collected in two specialized orthopedic centers. PJI were divided into acute (n = 33) and low-grade (n = 32) according to previously published classification. An activity assay specific for active MPO was performed in each sample. Ability of MPO to correctly discriminate patients with PJI from AF was determined by ROC analysis. The best discriminating cut-off value was determined by calculating the J Youden index. For all analyses, a P value < 0.05 was considered statistically significant.

Results

Active MPO was higher in PJI than AF (P < 0.0001). The ROC analysis revealed a significant area under the curve (AUC: 0.86; 95% CI: 0.78-0.93, P < 0.0001). A cut-off value of 561.9 U/mL, with good sensitivity (0.69) and specificity (0.88), discriminated between AF and PJI (accuracy 75.76%, 95% CI: 66.11-83.81%, positive likelihood ratio 5.88, 95% CI: 2.31-14.98 and negative likelihood ratio 0.35, 95%CI: 0.24-0.51). No difference in MPO levels was found between acute and chronic low-grade PJI.

Conclusion

The proposed assay appears to be a reliable and affordable tool for detecting the active MPO in synovial fluid, with promising characteristics of sensitivity and specificity in discriminating both acute and low-grade PJI from AF. Further studies are needed to confirm MPO diagnostic cut-off values and validate their use in the routine clinical practice.

Results of a monocentric field study: value of histology compared to sonication method and conventional tissue culture in the diagnosis of periprosthetic joint infection (PJI)

BACKGROUND

To confirm the diagnosis of periprosthetic joint infection (PJI), the Infectious Diseases Society of America (IDSA) and the International Consensus Meeting (ICM) have defined criteria that include histology as a minor criterion and the sonication method only as an additional criterion. The aim of this monocentric, retrospective study was to investigate the value of histology and whether sonication leads to a more accurate diagnosis.

MATERIALS AND METHODS

All revision surgeries for knee and hip arthroplasty between 2017 and 2020 were included. With regard to microbiological diagnostic, conventional culture of periprosthetic biopsies and sonication of explant material were performed. In addition, histology and non-specific inflammatory markers (CRP, leukocytes) were recorded.

RESULTS

A total of 78 patients with PJI and 62 aseptic controls were included. From both microbiological methods (conventional culture / sonication), Staphyloccus (S.) epidermidis and S. aureus were detected most frequently. However, compared to the conventional microbiology, a higher sensitivity was calculated for sonication, albeit with a lower specificity in relation to a PJI. In two logistic regression models for the significance of all diagnostic parameters in PJI, the AUC was 0.92 and 0.96 with histology in particular making the decisive contribution in both models (p < 0. 001, both models).

CONCLUSION

Since histology showed the highest accuracy in the current study, its importance in the PJI criteria should be reevaluated. Sonication shows a high sensitivity for germ detection with a lower specificity and should only be used in combination with the conventional culture for microbiolgical diagnostics.

Interleukin-1β Polymorphisms Are Genetic Markers of Susceptibility to Periprosthetic Joint Infection in Total Hip and Knee Arthroplasty

Periprosthetic joint infections (PJIs) are serious complications of prosthetic surgery. The criteria for the diagnosis of PJI integrate clinical and laboratory findings in a complex and sometimes inconclusive workflow. Host immune factors hold potential as diagnostic biomarkers in bone and joint infections. We reported that the humoral pattern-recognition molecule long pentraxin 3 (PTX3) predicts PJI in total hip and knee arthroplasty (THA and TKA, respectively). If and how genetic variation in PTX3 and inflammatory genes that affect its expression (IL-1β, IL-6, IL-10, and IL-17A) contributes to the risk of PJI is unknown. We conducted a case-control study on a Caucasian historic cohort of THA and TKA patients who had prosthesis explant due to PJI (cases) or aseptic complications (controls). Saliva was collected from 93 subjects and used to extract DNA and genotype PTX3, IL-1β, IL-6, IL-10, and IL-17A single-nucleotide polymorphisms (SNPs). Moreover, the concentration of IL-1β, IL-10, and IL-6 was measured in synovial fluid and plasma. No association was found between PTX3 polymorphisms and PJI; however, the AGG haplotype, encompassing rs2853550, rs1143634, and rs1143627 in IL-1β, was linked to the infection (p = 0.017). Also, synovial levels of all inflammatory markers were higher in cases than in controls, and a correlation emerged between synovial concentration of PTX3 and that of IL-1β in cases only (Spearman r = 0.67, p = 0.004). We identified a relationship between rs2853550 and the synovial concentration of IL-1β and PTX3. Our findings suggest that IL-1β SNPs could be used for the early identification of THA and TKA patients with a high risk of infection.

Hybrid Impedimetric Biosensors for Express Protein Markers Detection

Impedimetric biosensors represent a powerful and promising tool for studying and monitoring biological processes associated with proteins and can contribute to the development of new approaches in the diagnosis and treatment of diseases. The basic principles, analytical methods, and applications of hybrid impedimetric biosensors for express protein detection in biological fluids are described. The advantages of this type of biosensors, such as simplicity and speed of operation, sensitivity and selectivity of analysis, cost-effectiveness, and an ability to be integrated into hybrid microfluidic systems, are demonstrated. Current challenges and development prospects in this area are analyzed. They include (a) the selection of materials for electrodes and formation of nanostructures on their surface; (b) the development of efficient methods for biorecognition elements' deposition on the electrodes' surface, providing the specificity and sensitivity of biosensing; (c) the reducing of nonspecific binding and interference, which could affect specificity; (d) adapting biosensors to real samples and conditions of operation; (e) expanding the range of detected proteins; and, finally, (f) the development of biosensor integration into large microanalytical system technologies. This review could be useful for researchers working in the field of impedimetric biosensors for protein detection, as well as for those interested in the application of this type of biosensor in biomedical diagnostics.