Combined serum biomarker analysis shows no benefit in the diagnosis of periprosthetic joint infection

Current relevance of biomarkers in diagnosis of periprosthetic joint infection: an update

With a significant rise in the number of arthroplasty procedures performed worldwide, the increasing revision burden posed by periprosthetic joint infection (PJI) is a matter of growing concern. In spite of various attempts to diagnose PJI, there are no defined tests that can be called a gold standard. Given the importance of early diagnosis in PJI, newer tests and biomarkers have been introduced to improve cumulative diagnostic accuracy. Novel biomarkers like calprotectin, lipocalcin, monocyte-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio and platelet-to-mean platelet volume ratio have demonstrated a potential as diagnostic biomarkers for PJI. This article discusses the relevance of available and newly described diagnostic biomarkers to provide a perspective on the practical applicability in current medical practice, as well as highlights some recent advances in biomarkers for the diagnosis of PJI.

Interval between two-stage exchanges: what is optimal and how do you know?

BACKGROUND

Two-stage exchange arthroplasty remains the most popular option for the treatment of chronic periprosthetic joint infection (PJI). Determining infection eradication and optimal timing of reimplantation can be challenging. Information to allow for a truly informed evidence-based decision is scarce.

METHODS

We conducted a critical review of available evidence on the presently available tests to help determine timing of reimplantation.

RESULTS

Serology is traditionally used to follow up patients after the first stage. Despite tradition mandates waiting for normal inflammatory markers, there is actually no evidence that they correlate with persistent infection. The role of synovial fluid investigation between stages is also explored. Cultures lack sensitivity and neither differential leukocyte counts nor alternative biomarkers have proven to be accurate in identifying persistent infection with a spacer in situ. We also examined the evidence regarding the optimal time interval between resection and reimplantation and whether there is evidence to support the implementation of a two week "antibiotic holiday" prior to proceeding with reimplantation. Finally, wound healing and other important factors in this setting will be discussed.

CONCLUSION

Currently there are no accurate metrics to aid in the decision on the optimal timing for reimplantation. Decision must therefore rely on the resolution of clinical signs and down trending serological and synovial markers.

Diagnosis of Periprosthetic Joint Infection: The Utility of Biomarkers in 2023

Periprosthetic joint infection (PJI) is a rare yet devastating complication following total joint arthroplasty (TJA). Early and accurate diagnosis of PJI is paramount in order to maximize the chances of successful treatment. However, we are yet to identify a single "gold standard" test for the diagnosis of PJI. As a result, the diagnosis of PJI is often challenging. Currently, the 2018 ICM definition of PJI is the only validated diagnostic criteria available. This article will review the importance of serum and synovial biomarkers in the diagnosis of PJI. In addition, it will provide a brief overview of the emerging modalities for the identification of infections in this setting.

Serum versus synovial fluid interleukin-6 for periprosthetic joint infection diagnosis: a systematic review and meta-analysis of 30 diagnostic test accuracy studies

BACKGROUND

Early and accurate detection of periprosthetic joint infection (PJI) after hip and/or knee arthroplasty remains challenging. This systematic review and meta-analysis of diagnostic test accuracy studies aimed to evaluate the diagnostic accuracy of serum and synovial fluid interleukin (IL)-6 in detecting PJI.

METHODS

We searched 3 databases for studies through December 31, 2021, using medical sub-headings terms and keywords. Studies reported sensitivity and specificity of serum and synovial fluid IL-6 in detecting PJI were considered. We calculated the pooled sensitivity, specificity, positive and negative likelihood ratio, diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic curve (AUC) to evaluate the diagnostic accuracy of serum and synovial fluid IL-6.

RESULTS

Thirty studies were included. The pooled sensitivity, specificity, positive and negative likelihood ratio, DOR, and AUC of serum IL-6 in detecting PJI were 0.76 (0.69-0.81), 0.88 (0.82-0.92), 6.2 (4.3-9.0), 0.28 (0.22-0.35), 22 (14-36), and 0.88 (0.85-0.91), respectively. However, synovial fluid IL-6 achieved a pooled sensitivity of 0.87 (0.75-0.93), specificity of 0.90 (0.85-0.93), positive and negative likelihood ratio of 8.5 (5.3-13.6) and 0.15 (0.08-0.29), DOR of 57 (21-156), and AUC of 0.94 (0.92-0.96), which were higher than serum IL-6.

CONCLUSIONS

Synovial fluid IL-6 test may be a promising test for PJI after hip and/or knee arthroplasty. However, considering the limited volume of synovial fluid and invasive acquisition of synovial fluid IL-6, serum IL-6 test may be also considered.

Reliable Diagnostic Tests and Thresholds for Preoperative Diagnosis of Non-Inflammatory Arthritis Periprosthetic Joint Infection: A Meta-analysis and Systematic Review

Objective

The current diagnostic criteria for periprosthetic joint infection (PJI) are diverse and controversial, leading to delayed diagnosis. This study aimed to evaluate and unify their diagnostic accuracy and the threshold selection of serum and synovial routine tests for PJI at an early stage.

Methods

We searched the MEDLINE and Embase databases for retrospective or prospective studies which reported preoperative‐available assays (serum, synovial, or culture tests) for the diagnosis of chronic PJI among inflammatory arthritis (IA) or non‐IA populations from January 1, 2000 to June 30, 2022. Threshold effective analysis was performed on synovial polymorphonuclear neutrophils (PMN%), synovial white blood cell (WBC), serum C‐reactive protein (CRP), and erythrocyte sedimentation rate (ESR) to find the relevant cut‐offs.

Results

Two hundred and sixteen studies and information from 45,316 individuals were included in the final analysis. Synovial laboratory‐based α‐defensin and calprotectin had the best comprehensive sensitivity (0.91 [0.86–0.94], 0.95 [0.88–0.98]) and specificity (0.96 [0.94‐0.97], 0.95 [0.89–0.98]) values. According to the threshold effect analysis, the recommended cut‐offs are 70% (sensitivity 0.89 [0.85–0.92], specificity 0.90 [0.87–0.93]), 4100/μL (sensitivity 0.90 [0.87–0.93], specificity 0.97 [0.93–0.98]), 13.5 mg/L (sensitivity 0.84 [0.78–0.89], specificity 0.83 [0.73–0.89]), and 30 mm/h (sensitivity 0.79 [0.74–0.83], specificity 0.78 [0.72–0.83]) for synovial PMN%, synovial WBC, serum CRP, and ESR, respectively, and tests seem to be more reliable among non‐IA patients.

Conclusions

The laboratory‐based synovial α‐defensin and synovial calprotectin are the two best independent preoperative diagnostic tests for PJI. A cut off of 70% for synovial PMN% and tighter cut‐offs for synovial WBC and serum CRP could have a better diagnostic accuracy for non‐IA patients with chronic PJI.

Extra-pulmonary applications of procalcitonin: an updated literature review

INTRODUCTION

: Procalcitonin (PCT) is a biomarker with established performance in the differentiation between bacterial and viral infections, predominantly in pulmonary infections, as well as the diagnosis and prognosis of bacterial sepsis. However, the role of PCT in extra-pulmonary infections is not well described.

AREAS COVERED

: We reviewed the role of PCT in commonly experienced extra-pulmonary infections including meningitis, diabetic foot infection, prosthetic joint infection, osteomyelitis, and skin and soft tissue infection. PubMed and Medline online libraries were searched, from 2013 till 2022, for relevant articles.

EXPERT OPINION

: For meningitis, PCT could distinguish bacterial from viral meningitis. PCT distinguished septic arthritis from different types of arthritis but had variable performance in discriminating septic arthritis from crystal arthropathy. For periprosthetic joint infections, results were inconclusive. PCT had a potential role in diagnosis of more complex infections such as osteomyelitis and diabetic foot infections, but further studies are needed for a definitive cutoff. In skin and soft tissue infections, PCT performance was more variable requiring further investigation to define cutoff for the discrimination of cellulitis from necrotizing fasciitis. We find that PCT performed best for meningitis and helps in the reduction of unnecessary antibiotic treatment, but has variable outcomes with other extra-pulmonary infections.

Predicting the Exception-CRP and Primary Hip Arthroplasty

BACKGROUND

While primary hip arthroplasty is the most common operative procedure in orthopedic surgery, a periprosthetic joint infection is its most severe complication. Early detection and prediction are crucial. In this study, we aimed to determine the value of postoperative C-reactive protein (CRP) and develop a formula to predict this rare, but devastating complication.

METHODS

We retrospectively evaluated 708 patients with primary hip arthroplasty. CRP, white blood cell count (WBC), and several patient characteristics were assessed for 20 days following the operative procedure.

RESULTS

Eight patients suffered an early acute periprosthetic infection. The maximum CRP predicted an infection with a sensitivity and specificity of 75% and 56.9%, respectively, while a binary logistic regression reached values of 75% and 80%. A multinominal logistic regression, however, was able to predict an early infection with a sensitivity and specificity of 87.5% and 78.9%. With a one-phase decay, 71.6% of the postoperative CRP-variance could be predicted.

CONCLUSION

To predict early acute periprosthetic joint infection after primary hip arthroplasty, a multinominal logistic regression is the most promising approach. Including five parameters, an early infection can be predicted on day 5 after the operative procedure with 87.5% sensitivity, while it can be excluded with 78.9% specificity.

Serum Inflammatory Biomarkers in the Diagnosis of Periprosthetic Joint Infections

Accurate preoperative diagnosis of periprosthetic joint infections (PJIs) can be very challenging, especially in patients with chronic PJI caused by low-virulence microorganisms. Serum parameters, such as serum C-reactive protein (CRP) or the erythrocyte sedimentation rate (ESR), are—among other diagnostic test methods—widely used to distinguish septic from aseptic failure after total hip or knee arthroplasty and are recommended by the AAOS in the preoperative setting. However, they are systemic parameters, and therefore, unspecific. Nevertheless, they may be the first and occasionally the only preoperative indication, especially when clinical symptoms are lacking. They are easy to obtain, cheap, and are available worldwide. In the last decade, different novel serum biomarkers (percentage of neutrophils, neutrophils to lymphocytes ratio, platelet count to mean platelet volume ratio, fibrinogen, D-Dimer, Il-6, PCT) were investigated to find a more specific and accurate serum parameter in the diagnosis of PJI. This article reviews the diagnostic value of established (serum CRP, ESR, WBC) and ‘novel’ serum inflammatory biomarkers (fibrinogen, D-dimer, interleukin-6 (IL-6), procalcitonin, percentage of neutrophils (%N), neutrophils to lymphocytes ratio (NLR), platelet count to mean platelet volume ratio (PC/mPV)) for the preoperative diagnosis of periprosthetic joint infections.

Molecular sequencing technologies in the diagnosis and management of prosthetic joint infections

INTRODUCTION

Prosthetic joint infections (PJIs) can be challenging to eradicate and have high morbidity and mortality. Current microbiology culture methods can be associated with a high false-negative rate of up to 50%. Early and accurate diagnosis is crucial for effective treatment, and negative results have been linked to a greater rate of reoperation.

AREAS COVERED

There has been increasing investigation of the use of next-generation sequencing (NGS) technology such as metagenomic shotgun sequencing to help identify causative organisms and decrease the uncertainty around culture-negative infections. The clinical importance of the organisms detected and their management, however, requires further study. The polymerase chain reaction (PCR) has shown promise, but in recent years multiple studies have reported similar or lower sensitivity for bacteria detection in PJIs when compared to traditional culture. Furthermore, issues such as high cost and complexity of sample preparation and data analysis are to be addressed before it can move further toward routine clinical practice.

EXPERT OPINION

Metagenomic NGS has shown results that inspire cautious optimism - both in culture-positive and culture-negative cases of joint infection. Refinement of technique could revolutionize the way PJIs are diagnosed, managed, and drastically improve outcomes from this currently devastating complication.

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.

Reliability of circulating fibrinogen in the diagnosis of prosthesis-related infections: a systematic review and meta-analysis

Background

Fibrinogen (FIB) has recently been used as a biomarker to diagnose periprosthetic joint infection (PJI), but its reliability is still questionable. The aim of this study was to investigate the accuracy of FIB in the diagnosis of PJI after joint replacement.

Methods

We searched for literatures published in PubMed, EMBASE, and the Cochrane Library from the time of database inception to September 2020 and screened the studies according to the inclusion criteria. Then, we calculated the diagnostic parameters of FIB, including the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), area under the curve (AUC), and diagnostic odds ratio (DOR). In addition, we implemented subgroup analyses to identify the sources of heterogeneity.

Results

Seven studies including 1341 patients were selected in our meta-analysis. The pooled sensitivity, specificity, PLR, NLR, and DOR of FIB for PJI diagnosis were 0.78 (95% confidence interval [CI], 0.73–0.82), 0.83 (95% CI, 0.81–0.86), 4.60 (95% CI, 3.30–6.42), 0.24 (95% CI, 0.18–0.34), and 20.13 (95% CI, 14.80–27.36), respectively, while the AUC was 0.896.

Conclusion

The present study indicated that FIB was a reliable detection method and might be introduced into the diagnostic criteria for PJI. However, more robust studies are still needed to confirm the current findings, because most of the included studies were retrospective and had small sample sizes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-020-02171-x.

High platelet-to-lymphocyte ratio predicts poor survival of elderly patients with hip fracture

Purpose

The platelet-to-lymphocyte ratio (PLR) has been extensively studied in various diseases. However, the relationship between PLR and hip fracture remains unknown. The aim of this study was to evaluate whether PLR would be an independent prognostic factor in elderly hip fracture patients.

Methods

Between January 2014 and December 2018, a retrospective cohort study was conducted in a orthopaedic centre, China. A total of 460 hip fracture patients were included. PLR was calculated as the ratio of platelet to lymphocyte counts and divided into high PLR group (≥ 189) and low PLR group (< 189) by using the receiver operating characteristic (ROC) curve. The relationship between PLR and one year all-cause mortality rate was assessed by univariate and multivariate Cox proportional hazard models. Further subgroup analysis stratified by different clinical and biological characteristics was performed to make the results more accurate.

Results

After a median follow-up of 32.0 months (range, 12.0–75.4), 92 patients (mortality rate: 20.0%) died within one year. PLR was significantly higher in dead patients compared with alive patients (p < 0.05), and high PLR group also had a high mortality rate (32.21% vs. 14.15%, p < 0.001). After multivariate adjustment, high PLR remained an independent predictor for one year all-cause mortality (adjusted hazard ratio (HR) 1.56, 95% confidence interval (CI) 1.02–2.41, p = 0.041). Moreover, advanced age (HR 1.05, 95% CI 1.01–1.08), male (HR 1.62, 95% CI 1.06–2.45), CCI ≥ 2 (HR 2.83, 95% CI 1.64–4.89), conservative treatment (HR 5.94, 95% CI 3.71–9.73), low haemoglobin level (HR 1.02, 95% CI 1.01–1.04), and low albumin level (HR 1.07, 95% CI 1.02–1.13) were independent risk factors for survival. Furthermore, subgroup analysis results were consistent with the main findings in most stratified groups.

Conclusion

This study highlights that high PLR (≥ 189) is associated with increased one year all-cause mortality in elderly hip fracture patients. As PLR is a simple indicator that can be calculated from the blood routine test, it can be easily performed in usual clinical practice.