Diagnostic Accuracy of the Alpha-Defensin Test for Periprosthetic Joint Infection in Patients With Inflammatory Diseases

Performance of α-Defensins in Diagnosing Nosocomial Ventriculitis

Nosocomial ventriculitis can be an extremely difficult infectious disease process to diagnose, thereby exposing patients to increased morbidity and unwarranted aggressive antibiotics. Thus, novel ventriculitis diagnostics are drastically needed. In this study, we demonstrate excellent sensitivity and specificity of cerebral spinal fluid α-defensins to aid in diagnosing ventriculitis.

Efficacy analysis of clinical serological indicators in the diagnosis of postoperative periprosthetic joint infection in patients with rheumatoid arthritis or osteoarthritis

PURPOSE

To investigate the incidence of periprosthetic joint infection (PJI) in patients with rheumatoid arthritis (RA) or osteoarthritis (OA) after primary joint arthroplasty; to analyze the optimal cut-off values of clinical serum markers C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and D-dimer for the diagnosis of PJI in RA patients; and to explore their diagnostic efficacy and clinical significance.

METHODS

Clinical data of 15,702 patients with RA (578) or OA (15,124) who underwent total joint arthroplasty from 2013 to 2021 were retrospectively analyzed. Serum CRP, ESR, and D-dimer were recorded for each patient, and subject characteristic curves were used to determine the optimal threshold values of CRP, ESR, and D-dimer for RA-PJI and OA-PJI and to compare the areas under the curves to assess the diagnostic efficacy of the optimal threshold values of serologic indices for RA-PJI.

RESULTS

The five year incidence of PJI was 6.92% in RA patients and 0.67% in OA patients. The optimal thresholds of CRP, ESR, and D-dimer for the diagnosis of RA-PJI were respectively 13.85 mg/L, 33.02 mm/h, and 796.50 ng/mL. The sensitivities of the optimal thresholds were respectively 67.6%, 62.2%, and 56.8%, and the specificities were 74.7%, 60.4%, and 74.4%.

CONCLUSION

RA patients have a higher incidence of PJI than OA patients. The optimal thresholds for CRP, ESR, and d-dimer for the diagnosis of PJI were higher in RA patients than in OA patients, but the sensitivity and specificity of the diagnosis were not as good as in OA patients.

Update on the role of pathology and laboratory medicine in diagnosing periprosthetic infection

Technological and implant design advances have helped reduce the frequency of aseptic total joint arthroplasty failure, but periprosthetic joint infections (PJI) remain a clinical important problem with high patient morbidity. Misinterpreting PJI as aseptic mechanical loosening commonly leads to unsatisfactory revision arthroplasty, persistent infection, and poor long-term results. While there is no single "gold standard" diagnostic test for PJI, recent collaborative efforts by Orthopaedic and Infectious Disease Societies have developed algorithms for diagnosing PJI. However, the efficacy of individual tests as well as diagnostic thresholds are controversial. We review the recommended thresholds for commonly used screening tests as well as tissue histopathology and confirmatory tests to diagnose periprosthetic infection. We also update lesser-known laboratory tests, and we briefly summarize rapidly evolving molecular tests to diagnose periprosthetic infection. Pathologists hold a critical role in assisting with PJI diagnosis, maintaining laboratory test quality and interpreting test results. Collaboration between clinicians and pathologists is essential to provide optimal patient care and reduce the burden of PJI.

Diagnosing periprosthetic joint infection

Aims

The diagnosis of periprosthetic joint infection (PJI) can be challenging as the symptoms are similar to other conditions, and the markers used for diagnosis have limited sensitivity and specificity. Recent research has suggested using blood cell ratios, such as platelet-to-volume ratio (PVR) and platelet-to-lymphocyte ratio (PLR), to improve diagnostic accuracy. The aim of the study was to further validate the effectiveness of PVR and PLR in diagnosing PJI.

Methods

A retrospective review was conducted to assess the accuracy of different marker combinations for diagnosing chronic PJI. A total of 573 patients were included in the study, of which 124 knees and 122 hips had a diagnosis of chronic PJI. Complete blood count and synovial fluid analysis were collected. Recently published blood cell ratio cut-off points were applied to receiver operating characteristic curves for all markers and combinations. The area under the curve (AUC), sensitivity, specificity, and positive and negative predictive values were calculated.

Results

The results of the analysis showed that the combination of ESR, CRP, synovial white blood cell count (Syn. WBC), and polymorphonuclear neutrophil percentage (PMN%) with PVR had the highest AUC of 0.99 for knees, with sensitivity of 97.73% and specificity of 100%. Similarly, for hips, this combination had an AUC of 0.98, sensitivity of 96.15%, and specificity of 100.00%.

Conclusion

This study supports the use of PVR calculated from readily available complete blood counts, combined with established markers, to improve the accuracy in diagnosing chronic PJI in both total hip and knee arthroplasties.

Role of α-Defensin and the Microbiome in Prosthetic Joint Infection: A Prospective Cohort Study in Korea

The utility of α-defensin (AD), leukocyte esterase (LE) levels, and metagenomics sequencing as diagnostic tools for prosthetic joint infection (PJI) has been suggested, but there are few studies among the Asian population. This study aimed to evaluate the diagnostic performance of various biomarkers for PJI and the role of the microbiome in the synovial fluid of patients with prostheses. Patients with suspected knee PJI were enrolled, and their blood and synovial fluid were collected. The cases were classified into the PJI and non-PJI groups. Significant differences between the two groups were observed in the levels of AD (4698 µg/L vs. 296 µg/L, p < 0.001) and positivity for LE (62.5% vs. 21.1%, p = 0.01). AD had 94.4% sensitivity and 89.5% specificity for diagnosing PJI, whereas LE had 37.5% sensitivity and 100% specificity. Microbiome taxonomic profiling showed high sensitivity. The number of operational taxonomic units and the richness of the microbiome in the synovial fluid were higher in the non-PJI than in the PJI group. AD has shown encouraging results in the Asian population as a diagnostic biomarker for PJI, and LE can be used as a diagnostic adjunct. The bacterial richness of the synovial fluid is likely associated with infections.

C-reactive protein (CRP)/albumin-to-globulin ratio (AGR) is a valuable test for diagnosing periprosthetic joint infection: a single-center retrospective study

Background

The diagnosis of periprosthetic joint infection (PJI) is challenging for clinicians, and the commonly used methods are too complicated and expensive for many clinical practices. The neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), the platelet–to-mean-platelet-volume ratio (PVR), globulin (GLB), the albumin-to-globulin ratio (AGR), and the C-reactive protein (CRP)/AGR ratio are simple biomarkers for infection and can be easily determined from routine blood tests. Due to their low cost and ready availability in clinical practice, many clinicians have considered the diagnostic value of these biomarkers for PJI. The aim of our study is to determine the value of NLR, PLR, PVR, GLB, AGR, and CRP/AGR for the diagnosis of PJI.

Materials and methods

One hundred sixty-four patients who received revision surgery after total knee or total hip replacements were enrolled, 47 in a PJI group and 117 in an aseptic failure group. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of NLR, PLR, PVR, GLB, AGR, and CRP/AGR for the diagnosis of PJI, and their performance levels were then compared with those of CRP and the erythrocyte sedimentation rate (ESR).

Results

The levels of all tested biomarkers were significantly higher in patients with PJI (all P < 0.05). ROC analysis showed that CRP/AGR performed best in diagnosing PJI, with an area under curve (AUC) value of 0.902, and the AUCs of NLR (0.740), PLR (0.721), PVR (0.668), GLB (0.719), and AGR (0.767) were all lower than those for CRP (0.896) and ESR (0.829).

Conclusion

CRP/AGR was a valuable test for diagnosing PJI, but other novel biomarkers had only limited diagnostic value.

Level of Evidence

Level III

Synovial fluid α defensin has comparable accuracy to synovial fluid white blood cell count and polymorphonuclear percentage for periprosthetic joint infection diagnosis

AIMS

The aim of this study was to determine the diagnostic accuracy of α defensin (AD) lateral flow assay (LFA) and enzyme-linked immunosorbent assay (ELISA) tests for periprosthetic joint infection (PJI) in comparison to conventional synovial white blood cell (WBC) count and polymorphonuclear neutrophil percentage (PMN%) analysis.

METHODS

Patients undergoing joint aspiration for evaluation of pain after total knee arthroplasty (TKA) or total hip arthroplasty (THA) were considered for inclusion. Synovial fluids from 99 patients (25 THA and 74 TKA) were analyzed by WBC count and PMN% analysis, AD LFA, and AD ELISA. WBC and PMN% cutoffs of ≥ 1,700 cells/mm³ and ≥ 65% for TKA and ≥ 3,000 cells/mm³ and ≥ 80% for THA were used, respectively. A panel of three physicians, all with expertise in orthopaedic infections and who were blinded to the results of AD tests, independently reviewed patient data to diagnose subjects as with or without PJI. Consensus PJI classification was used as the reference standard to evaluate test performances. Results were compared using McNemar's test and area under the receiver operating characteristic curve (AUC) analysis.

RESULTS

Expert consensus classified 18 arthroplasies as having failed due to PJI and 81 due to aseptic failure. Using these classifications, the calculated sensitivity and specificity of AD LFA was 83.3% (95% confidence interval (CI) 58.6 to 96.4) and 93.8% (95% CI 86.2 to 98.0), respectively. Sensitivity and specificity of AD ELISA was 83.3% (95% CI 58.6 to 96.4) and 96.3% (95% CI 89.6 to 99.2), respectively. There was no statistically significant difference between sensitivity (p = 1.000) or specificity (p = 0.157) of the two AD assays. AUC for AD LFA was 0.891. In comparison, AUC for synovial WBC count, PMN%, and the combination of the two values was 0.821 (sensitivity p = 1.000, specificity p < 0.001), 0.886 (sensitivity p = 0.317, specificity p = 0.011), and 0.926 (sensitivity p = 0.317, specificity p = 0.317), respectively.

CONCLUSION

The diagnostic accuracy of synovial AD for PJI diagnosis is comparable and not statistically superior to that of synovial WBC count plus PMN% combined. Cite this article: Bone Joint J 2021;103-B(6):1119-1126.

Plasma fibrinogen in the diagnosis of periprosthetic joint infection

Periprosthetic joint infections (PJIs) have become the most catastrophic complication for patients after arthroplasty. Although previous studies have found that many biomarkers have good performance for diagnosing PJI, early diagnosis remains challenging and a gold standard is lacking. This study aimed to investigate the diagnostic accuracy of plasma fibrinogen (FIB) in detecting PJI compared to other traditional biomarks (CRP, WBC and ESR). A total of 156 patients (including 57 PJI and 99 non-PJI patients) who underwent revision arthroplasty were retrospectively reviewed from 01/2014 to 01/2020. The diagnostic criteria of PJI were mainly based on the definition from the evidence-based definition for periprosthetic joint infection in 2018. The optimal plasma FIB predictive cutoff was 4.20 g/L, the sensitivity of the plasma fibrinogen was 0.860, the specificity was 0.900, the positive predictive value (PPV) was 0.831, and the negative predictive value (NPV) was 0.908. The area under the curve (AUC) value of plasma fibrinogen was 0.916 (95% CI 0.869-0.964), and the CRP, ESR and WBC levels had AUCs of 0.901, 0.822 and 0.647, respectively. Plasma FIB demonstrated better diagnostic strength compared with that of other serum biomarkers before revision arthroplasty. It represents a new horizon for the diagnosis of PJI due to the diagnosis values and cost-effective features.

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.

Does the Alpha Defensin ELISA Test Perform Better Than the Alpha Defensin Lateral Flow Test for PJI Diagnosis? A Systematic Review and Meta-analysis of Prospective Studies

BACKGROUND

Periprosthetic joint infection (PJI) following total joint arthroplasty is a serious complication that causes severe morbidity and adds a major financial burden to the healthcare system. Although there is plenty of research on the alpha-defensin (AD) test, a meta-analysis consisting of only prospective studies investigating AD's diagnostic efficacy has not been performed. Additionally, some important subgroups such as THA and TKA have not been separately analyzed, particularly regarding two commonly used versions of the AD test, the laboratory-based (ELISA) and lateral-flow (LF).

QUESTIONS/PURPOSES

(1) Does the AD ELISA test perform better in the detection of PJI than the AD LF test, in terms of pooled sensitivity and specificity, when including prospective studies only? (2) Are there differences in sensitivity or specificity when using AD ELISA and AD LF tests for PJI diagnosis of THA or TKA PJI separately?

METHODS

Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines, we included prospective studies describing the use of either AD test in the workup of pain after total joint arthroplasty (primary or revision, but not after resection arthroplasty). Fifteen studies (AD ELISA: 4; AD LF: 11) were included, with 1592 procedures. Subgroup data on THA and TKA could be retrieved for 1163 procedures (ELISA THA: 123; LF THA: 257; ELISA TKA: 228; LF TKA: 555). Studies not describing THA or TKA, those not using Musculoskeletal Infection Society (MSIS) criteria as the standard for determining the presence or absence of PJI, those not clearly reporting data for the AD test for the total cohort, and those describing data published in another study were excluded. Studies were not excluded based on follow-up duration; the MSIS criteria could be used within a few weeks, when test results were available. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 criteria. Study quality was generally good. The most frequent sources of bias were related to patient selection (such as unclear inclusion and exclusion criteria) and flow and timing (uncertainty in place and time of aspiration, for example). Heterogeneity was moderate to high; a bivariate random-effects model therefore was used. To answer both research questions, sensitivity and specificity were calculated for AD ELISA and LF test groups and THA and TKA subgroups, and were compared using z-test statistics and meta-regression analysis.

RESULTS

No differences were found between the AD ELISA and the AD LF for PJI diagnosis in the pooled cohorts (THA and TKA combined), in terms of sensitivity (90% versus 86%; p = 0.43) and specificity (97% versus 96%; p = 0.39). Differences in sensitivity for PJI diagnosis were found between the THA and TKA groups for the AD ELISA test (70% versus 94%; p = 0.008); pooled AD LF test sensitivity did not differ between THA and TKA (80% versus 87%; p = 0.20). No differences in specificity were found in either subgroup.

CONCLUSIONS

Both the AD ELISA and AD LF test can be used in clinical practice because both have high sensitivity and very high specificity for PJI diagnosis. The lower sensitivity found for diagnosis of PJI in THA for the AD ELISA test must be carefully interpreted because the pooled data were heterogenous and only two studies for this group were included. Future research should analyze TKAs and THAs separately to confirm or disprove this finding.

LEVEL OF EVIDENCE

Level II diagnostic study.