The Role of Biomarkers for the Diagnosis of Implant-Related Infections in Orthopaedics and Trauma

Emerging Technologies in Diagnosing Periprosthetic Joint Infections

Periprosthetic joint infection (PJI) is a well-known serious complication following joint replacement surgeries and is responsible for high failure rates of implanted devices. Any delay in the diagnosis can compromise treatment success, putting a huge burden on the patients' wellness and healthcare systems. Diagnosing PJIs is quite complex as there is still no gold standard test to reach the definitive diagnosis in a timely manner. A number of laboratory tests and radiological imaging inventions have evolved in the past few years, requiring consistent updates of the available guidelines to keep up with the latest advances in the field. This article highlights the recent advances in diagnosing PJIs and discusses their validity for use in clinical practice.

Microporous Implants Modified by Bifunctional Hydrogel with Antibacterial and Osteogenic Properties Promote Bone Integration in Infected Bone Defects

Prosthesis implantation and bone integration under bacterial infection are arduous challenges in clinical practice. It is well known that the reactive oxygen species (ROS) produced by bacterial infection around the bone defects will further hinder bone healing. To solve this problem, we prepared a ROS-scavenging hydrogel by cross-linking polyvinyl alcohol and a ROS-responsive linker, N¹-(4-boronobenzyl)-N³-(4-boronophenyl)-N¹, N¹, N³, N³-tetramethylpropane-1, 3-diaminium, to modify the microporous titanium alloy implant. The prepared hydrogel was used as an advanced ROS-scavenging tool to promote bone healing by inhibiting the ROS levels around the implant. Bifunctional hydrogel serving as a drug delivery system can release therapeutic molecules, including vancomycin, to kill bacteria and bone morphogenetic protein-2 to induce bone regeneration and integration. This multifunctional implant system that combines mechanical support and disease microenvironment targeting provides a novel strategy for bone regeneration and integration of implants in infected bone defects.

Current and novel diagnostics for orthopedic implant biofilm infections: a review

Biofilm infections involving orthopedic implants are a global problem. They contribute to severe complications and mortality, as well as increased use of antibiotic treatments and development of antibiotic-resistant microorganisms. More than 1 million hip and knee arthroplasties are performed each year in the United States. These hard-to-treat infections lead to patient distress, increased morbidity, and high financial costs to both patients and healthcare systems. There is a need to improve the diagnosis of such biofilm infections to allow for earlier detection and treatment. Current diagnostics rely on clinical signs for infections such as loss of function, fever, rubor, patient history of the predisposing condition, persisting infection, failure of antibiotic treatment, and documentation of antibiotic failure. Below, we present a framework which outlines the data gaps in the conventional laboratory techniques used in clinical diagnostics; we also discuss promising novel diagnostic methods which are currently used solely in research. It is critical to assess these novel infection diagnostic techniques and address the data gaps and clinical hesitance preventing application in a clinical setting. Additionally, the combination of conventional and novel diagnostic technologies would streamline the diagnostic process of biofilm infections associated with orthopedic implants.

Serum and Synovial Biomarkers for the Diagnosis of Implant-Associated Infection After Orthopedic Surgery

Implant-associated infection is one of the most devastating complications following orthopedic surgery. Early identification is crucial for treatment. Currently, however, a reliable diagnostic tool is lacking, partly due to disparate bacteria colonies (virulent vs non-virulent), difficulty in distinguishing infection from inflammatory disease, and highly diverse diagnostic thresholds and testing methods. Given the importance of biomarkers in the initial screening for the infection, an extensive effort has been made to develop serum and synovial biomarkers. In this review, the authors summarize the results from the most relevant studies to provide comprehensive information on biomarkers for the diagnosis of implant-associated infection. [Orthopedics. 2021;44(2):e158-e166.].

Diagnostic value of next-generation sequencing to detect periprosthetic joint infection

Background

We herein compared the diagnostic value of next-generation sequencing (NGS), bacterial culture, and serological biomarkers to detect periprosthetic joint infection (PJI) after joint replacement.

Methods

According to the diagnostic criteria of the Musculoskeletal Infection Society, 35 patients who underwent joint revision surgery were divided into infection (15 cases) and non-infection (20 cases) groups, and were routinely examined preoperatively for erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and D-dimer levels. All patients underwent arthrocentesis preoperatively. Synovial fluid was used for white blood cell count, white blood cell classification, bacterial culture, and NGS. Furthermore, we calculated the area under the curve (AUC) of the receiver operating characteristic curve (ROC) for ESR, CRP, PCT, IL-6, and D-dimer. Data were assessed by comparing diagnostic accuracy, sensitivity, and specificity.

Results

Fourteen patients showed positive results by NGS and seven showed positive bacterial culture results in the infection group; further, 18 showed negative results by NGS in the non-infection group. The AUC of ESR, D-dimer, CRP, IL-6, and PCT was 0.667, 0.572, 0.827, 0.767, and 0.808, respectively. The accuracy of NGS, bacterial culture, CRP, IL-6, and PCT was 0.91, 0.74, 0.77, 0.74, and 0.83, respectively. When comparing NGS with CRP, IL-6, PCT, and bacterial culture, differences in overall test results and those in sensitivity were statistically significant, and compared with CRP, differences in specificity were also statistically significant. In comparison with IL-6, PCT, and bacterial culture, the specificity of NGS was statistically insignificant.

Conclusions

Our results indicated that NGS had higher accuracy and sensitivity than the bacterial culture method and commonly used serological biomarkers for diagnosing PJI.

Circulating D-Dimer versus Fibrinogen in the Diagnosis of Peri-Prosthetic Joint Infection: A Meta-Analysis

Background: Circulating D-dimer and fibrinogen are both emerging as promising biomarkers for the diagnosis of peri-prosthetic joint infection (PJI), but their clinical values still remain disputable. This study aims to evaluate and compare the accuracy of circulating D-dimer and fibrinogen in the diagnosis of suspected PJI. Methods: We conducted a comprehensive literature search in PubMed, EMBASE, and the Cochrane Library to retrieve diagnostic accuracy studies in which PJI was investigated with circulating D-dimer or fibrinogen from the time of database inception to August 1, 2019. The pooled sensitivity, specificity, likelihood ratios and diagnostic odds ratio (DOR), summary receiver operating characteristic (sROC) curves, and area under the sROC curve (AUC) were constructed using a meta-analysis framework. Results: Seven eligible studies (1,374 patients) were included in the quantitative analysis. The mean levels of circulating D-dimer and fibrinogen were all significantly higher in patients with PJI. The plasma fibrinogen illustrated relatively higher sensitivity (0.84, 95% confidence interval [CI]: 0.78-0.98) and specificity (0.80, 95% CI: 0.76-0.84) than circulating D-dimer (0.74, 95% CI: 0.69-0.78; 0.66, 95% CI: 0.62-0.69, respectively) for the diagnosis of PJI. The pooled DOR of D-dimer, fibrinogen, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) to diagnose PJI was 7.00 (95% CI, 2.50-19.59), 12.40 (95% CI, 5.85 to 26.28), 10.71 (95% CI, 7.76 to 14.78) and 16.22 (95% CI 11.71-22.46), respectively, while the pooled AUC was 0.84 (95% CI, 0.77-0.90), 0.87 (95% CI, 0.85-0.89), 0.82 (95% CI, 0.78-0.85) and 0.87 (95% CI, 0.86-0.88), respectively. Conclusions: This meta-analysis reveals that it could be concluded that plasma fibrinogen is an excellent biomarker for diagnosing PJI, comparable to serum CRP and ESR, while the diagnostic value of circulating D-dimer is only moderate. Large-scale, prospective studies are still needed to confirm current findings.

What is the performance of novel synovial biomarkers for detecting periprosthetic joint infection in the presence of inflammatory joint disease?

AIMS

The aim of this study was to further evaluate the accuracy of ten promising synovial biomarkers (bactericidal/permeability-increasing protein (BPI), lactoferrin (LTF), neutrophil gelatinase-associated lipocalin (NGAL), neutrophil elastase 2 (ELA-2), α-defensin, cathelicidin LL-37 (LL-37), human β-defensin (HBD-2), human β-defensin 3 (HBD-3), D-dimer, and procalcitonin (PCT)) for the diagnosis of periprosthetic joint infection (PJI), and to investigate whether inflammatory joint disease (IJD) activity affects their concentration in synovial fluid.

METHODS

We included 50 synovial fluid samples from patients with (n = 25) and without (n = 25) confirmed PJI from an institutional tissue bank collected between May 2015 and December 2016. We also included 22 synovial fluid samples aspirated from patients with active IJD presenting to Department of Rheumatology, the first Medical Centre, Chinese PLA General Hospital. Concentrations of the ten candidate biomarkers were measured in the synovial fluid samples using standard enzyme-linked immunosorbent assays (ELISA). The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curves.

RESULTS

BPI, LTF, NGAL, ELA-2, and α-defensin were well-performing biomarkers for detecting PJI, with areas under the curve (AUCs) of 1.000 (95% confidence interval, 1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), 1.000 (1.000 to 1.000), and 0.998 (0.994 to 1.000), respectively. The other markers (LL-37, HBD-2, D-dimer, PCT, and HBD-3) had limited diagnostic value. For the five well-performing biomarkers, elevated concentrations were observed in patients with active IJD. The original best thresholds determined by the Youden index, which discriminated PJI cases from non-PJI cases could not discriminate PJI cases from active IJD cases, while elevated thresholds resulted in good performance.

CONCLUSION

BPI, LTF, NGAL, ELA-2, and α-defensin demonstrated excellent performance for diagnosing PJI. However, all five markers showed elevated concentrations in patients with IJD activity. For patients with IJD, elevated thresholds should be considered to accurately diagnose PJI. Cite this article: Bone Joint J 2021;103-B(1):32-38.

Analysis of synovial biomarkers with a multiplex protein microarray in patients with PJI undergoing revision arthroplasty of the hip or knee joint

INTRODUCTION

Diagnosing a (low-grade) periprosthetic joint infection (PJI) after hip or knee arthroplasty remains a diagnostic challenge. The aim of this study was to evaluate the utility of using a novel multiplex protein microarray system for synovial biomarkers in determining PJI in patients undergoing revision knee or hip arthroplasty.

MATERIALS AND METHODS

The individual synovial fluid levels of 12 cytokines (IL-1b, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, IL-17, GM-CSF, TNF-α, and INF-γ) were analysed with a novel multiplex protein microarray system in 32 patients undergoing revision hip (n = 22) or knee (n = 10) arthroplasty. Cases were classified into septic and aseptic groups on basis of pre- and interoperative findings: [PJI (n = 14) vs. non-PJI (n = 18)]. Receiver operator characteristic (ROC) curves were calculated to assess the discriminatory strength of the individual parameters. A multiple regression model was used to determine the utility of using a combination of the tested cytokines to determine the infection status.

RESULTS

The levels of all of the evaluated cytokines were significantly elevated in the PJI-group. Best sensitivity and specificity were found for IL-6, followed by IL-1b, IL-10, and IL-17. The multiple regression models revealed a combination of IL-2, IL-4, IL-5, IL6, lL-12, and GM-CSF to be associated with the best sensitivity (100%) and specificity (88.9%) for a cut-off value of 0.41, with a likelihood ratio of 9.0.

CONCLUSION

Analysis of individual synovial fluid cytokine levels showed both high sensitivity and high specificity in diagnosing PJI. A combined model using several cytokines showed even higher sensitivity and specificity in diagnosing PJI and could thus be a useful predictive tool to determine the probability of PJI in patients with a painful prosthesis.

LEVEL OF EVIDENCE

Diagnostic IV.

Plasma d-Dimer Levels in Non-prosthetic Orthopaedic Implant Infection: Can it Aid Diagnosis?

PURPOSE

d-Dimer estimation has been proposed as a reliable biomarker in prosthetic joint infections. Its role in non-prosthetic orthopaedic implant infections has, however, not been studied. The objectives of this study were to assess the levels of plasma d-Dimer in non-prosthetic orthopaedic implant infection. The diagnostic efficiency of d-dimer on orthopaedic implant-related infection was evaluated.

METHODS

The study was designed as a cross-sectional comparative study. Patients who presented with orthopaedic implant-related infection as diagnosed by modified MSIS criteria were allocated to case group (n = 49) and patients who underwent surgical procedures with orthopaedic implants with no evidence of infection at 6 weeks postoperatively were allocated to the control group (n = 48). Serum d-Dimer levels were assessed quantitatively using immunoturbidimetric assays in both groups and compared between both groups.

RESULTS

The mean (± SD) value of serum d-Dimer in case group was 0.64 (± 0.45) μg/ml and control group was 0.77 (± 0.47) μg/ml. No significant difference was found in serum d-Dimer levels between cases and control groups (p value = 0.183). The diagnostic accuracy of d-dimer in orthopaedic implant-related infection also could not be demonstrated.

CONCLUSION

The findings of d-dimer as a marker for the diagnosis of prosthetic joint infections cannot be extrapolated to non-prosthetic orthopaedic implant infection.

New Imaging, Diagnostic, and Assessment Techniques in Orthopedic Trauma

This article examines new imaging, diagnostic, and assessment techniques that may affect the care of patients with orthopedic trauma and/or infection. Three-dimensional imaging has assisted in fracture assessment preoperatively, whereas improvement in C-arm technology has allowed real-time evaluation of implant placement and periarticular reduction before leaving the operating room. Advances in imaging techniques have allowed earlier and more accurate diagnosis of nonunion and infection. Innovations in bacteriologic testing have improved the sensitivity and specificity of perioperative and peri-implant infections. It is critical that surgeons remain up to date on the options available for optimal patient care.

Prevention and detection of prosthetic temporomandibular joint infections-update

Prosthetic joint infections are not only distressing complications for patients and surgeons, but also have an enormous financial impact on healthcare systems. The reported incidence of prosthetic joint infection is likely underestimated due to difficulties in their diagnosis. This unfortunate complication has challenged joint replacement surgeons for years, despite all the advances made in this surgical discipline. Since eradication of these infections can be very difficult, prevention remains the primary objective. Identifying recipient risk factors, adopting a proper surgical technique, appropriate wound care, optimizing the operating room environment, and appropriate postoperative care have become some of the core elements that can help to minimize the overall incidence of this complication. The purpose of this article is to provide the temporomandibular joint replacement surgeon with an update on the prevention and detection of prosthetic joint infections based on a review of the most recent information published in the orthopedic and surgical literature.

Current Recommendations for the Diagnosis of Acute and Chronic PJI for Hip and Knee-Cell Counts, Alpha-Defensin, Leukocyte Esterase, Next-generation Sequencing

PURPOSE OF REVIEW

Despite significant progress in recent years, the diagnosis of periprosthetic joint infection (PJI) remains a challenge and no gold standard test exists. A combination of serological, synovial, microbiological, histological, and radiological investigations is performed that are expensive, often invasive, and imperfect. Novel biomarkers and molecular methods have shown promise in recent years. The purpose of this review is to provide an update about the diagnostic recommendations for PJI and cover a selection of emerging diagnostic tools.

RECENT FINDINGS

Recent literature highlights a new evidence-based definition for diagnosing hip and knee PJI that shows excellent performance on formal external multi-institutional validation. There is also increasing evidence to support the measurement of selected biomarkers in serum and synovial fluid, such as alpha-defensin, D-dimer, and interleukin-6. Finally, the emerging utility of next-generation sequencing for pathogen identification is discussed. In summary, we describe current recommendations and emerging tests for the diagnosis of PJI. Residual limitations and directions for future research are also discussed.

Prosthetic Joint Infections: an Update

PURPOSE OF REVIEW

Prosthetic joint infection (PJI) is a rare but serious complication that is frequently misdiagnosed. We aimed to highlight the nuances of PJI diagnosis and antimicrobial therapies and provide clarity in key areas of management.

RECENT FINDINGS

Current research in PJI centers on a potential role for diagnostic biomarkers, molecular techniques, and implant sonication to reduce culture-negativity rates. The optimal duration of antimicrobial therapy remains controversial. A high clinical index of suspicion for PJI combined with data from multiple preoperative and intraoperative tests enables timely diagnosis and treatment. Biomarkers, molecular methods, and implant sonication are currently adjunctive to traditional diagnostic techniques. Shorter courses of antimicrobial therapies as well as the role of chronic suppressive therapy need confirmation by randomized controlled trials. Existing practices for preoperative dental prophylaxis and treatment of asymptomatic bacteriuria warrant revision based on evidence arguing against risk for PJI.

Diagnostic accuracy of alpha-defensin in periprosthetic joint infection: a systematic review and meta-analysis

BACKGROUND

Alpha-defensin, a novel biomarker, has shown great potential for the accurate diagnosis of periprosthetic joint infection (PJI) in recent years: many published studies have presented encouraging results. Nevertheless, the diagnostic accuracy of alpha-defensin is inconsistent across published studies. Moreover, the optimum value of the diagnostic threshold urgently needs to be ascertained. This meta-analysis sought to estimate the precision of alpha-defensin for the diagnosis of PJI and, where possible, to confirm the threshold.

METHOD

We systematically searched PubMed, Embase, Cochrane, Web of Knowledge, and ClinicalTrials.gov for relevant literature on alpha-defensin in the diagnosis of PJI (searching publications from the inception of each database until February 2017, with no language restriction). Pooled sensitivity, specificity, diagnostic odds ratios, and likelihood ratios were the indexes used for assessment, with the use of a random-effects model.

RESULT

Eleven of the 426 studies that evaluated the diagnostic accuracy of alpha-defensin in periprosthetic joint infection (PJI) were included in this analysis. The pooled diagnostic sensitivity of alpha-defensin for PJI was 0.96 (95% confidence interval [CI], 0.87 to 0.99) and the specificity was 0.95 (95% CI, 0.91 to 0.97). Since there was substantial heterogeneity among studies, based on the inconsistency index (I²), threshold, site of arthroplasty, study design and techniques for the alpha-defensin test, subgroup analyses were performed to estimate the impacts of these variables on heterogeneity.

CONCLUSION

In summary, this meta-analysis clearly lends support to the conclusion that alpha-defensin is a promising addition to the current methods for diagnosis of PJI.