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.
Comparative analysis of 23 synovial fluid biomarkers for hip and knee periprosthetic joint infection detection
AbstractThere is interest in novel synovial fluid biomarkers for the detection of periprosthetic joint infection (PJI). Here, we assessed the diagnostic accuracy of 23 simple or sophisticated synovial fluid biomarkers for periprosthetic hip or knee infection detection. One hundred seven subjects were studied, 57 of whom had aseptic failure (AF) and 50 PJI. The following synovial fluid biomarkers were tested using spectrophotometric assays, immunoassays, lateral flow tests, or test strips: leukocyte count, monocyte percentage, lymphocyte percentage, neutrophil percentage, C‐reactive protein (CRP), glucose, lactate, granulocyte‐macrophage colony‐stimulating factor, interferon‐γ, interleukin‐1β (IL‐1β), IL‐2, IL‐4, IL‐5, IL‐6, IL‐8, IL‐10, IL‐12p70, IL‐13, IL‐17A, IL‐23, tumor necrosis factor‐α, α‐defensin, and leukocyte esterase. The best‐performing synovial fluid biomarkers to differentiate PJI from AF—that is, those with highest area under the curve compared to all other biomarkers—were leukocyte count, percent neutrophils and percent monocytes, CRP, and α‐defensin (P < .0001).
Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing
Metagenomic shotgun sequencing has the potential to transform how serious infections are diagnosed by offering universal, culture-free pathogen detection. This may be especially advantageous for microbial diagnosis of prosthetic joint infection (PJI) by synovial fluid analysis since synovial fluid cultures are not universally positive and since synovial fluid is easily obtained preoperatively.
Direct Detection and Identification of Prosthetic Joint Pathogens in Synovial Fluid (SF) by Metagenomic Shotgun Sequencing
Abstract Background Detection and identification of microorganism(s) involved in periprosthetic joint infection (PJI) can inform surgical management and directed antibiotic therapy. Metagenomic shotgun sequencing is a powerful tool with the potential to change how many PJIs are diagnosed as it allows direct detection and identification of pathogens in clinical specimens. In the largest series to date, we utilized a metagenomics-based approach applied to SF to define potential microbial etiologies of failed total knee arthroplasties (TKAs). Methods Synovial fluid was collected from 112 failed TKAs [74 PJI and 38 aseptic implant failure (AF)] via preoperative arthrocentesis. Cell count and differential, standardized culture and DNA-based metagenomic shotgun sequencing were performed. Human DNA was depleted using the MolYsis basic kit prior to DNA extraction, whole genome amplification, and sequencing. Taxonomic assignment of reads and pathogen identification was achieved using a pipeline incorporating k-mer- and marker gene-based classification software. A scheme for analysis and filtration of false-positives was created and applied, incorporating cut-offs for the number of reads, quality scores, and coverage across a reference genome. Patients were classified as having PJI using the IDSA criteria and expert review. Analyses were recorded as percent agreement, with 95% confidence intervals (CI), of metagenomics to SF culture. Results Metagenomic analysis identified the known pathogen in 54 (90%) (CI, 79.5%–96.2%) of the 60 culture-positive PJIs analyzed and one (2%) (CI, 0.0%–8.9%) potential polymicrobial infection not detected by culture. For the 14 culture-negative PJIs tested, metagenomics showed 79% (CI, 49.2%–95.3%) agreement for negative findings; potential pathogens were identified in three (21%) (CI, 4.7%–50.8%) culture-negative PJI cases, with one being polymicrobial. Of the 37 culture-negative AF cases, metagenomics showed 97% (CI, 85.8%–99.9%) agreement with negative culture and identified one (3%) (CI, 0.0%–14.2%) potential pathogen. For the one culture-positive AF case, metagenomic results were negative, suggesting possible culture contamination. Conclusion Metagenomic shotgun sequencing performed on SF can be used to diagnose PJI and may be particularly useful for culture-negative PJI. Disclosures R. Patel, ASM: Board Member, None; CD Diagnostics, BioFire, Curetis, Merck, Hutchison Biofilm Medical Solutions, Accelerate Diagnostics, Allergan, and The Medicines Company: Grant Investigator, Grant recipient; Curetis: Consultant, Monies paid to my employer; A patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication with royalties paid by Samsung to Mayo Clinic, and a patent on an anti-biofilm substance issued: Patents, Patents, any money is paid to my employer; Actelion: DSMB, Money paid to my employer; ASM and IDSA: Editor’s stipends, Editor’s stipends; NBME, Up-to-Date and the Infectious Diseases Board Review Course: NBME, Up-to-Date and the Infectious Diseases Board Review Course, Honoraria; Roche, ASM, and IDSA: Travel reimbursement, Travel reimbursement