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SYMPOSIUM: 2013 MUSCULOSKELETAL INFECTION SOCIETY
Diagnosing Periprosthetic Joint Infection
Has the Era of the Biomarker Arrived?
Carl Deirmengian MD, Keith Kardos PhD,
Patrick Kilmartin, Alexander Cameron, Kevin Schiller,
Javad Parvizi MD
ÓThe Author(s) 2014. This article is published with open access at Springerlink.com
Abstract
Background The diagnosis of periprosthetic joint infection
(PJI) remains a serious clinical challenge. There is a pressing
need for improved diagnostic testing methods; biomarkers
offer one potentially promising approach.
Questions/purposes We evaluated the diagnostic charac-
teristics of 16 promising synovial fluid biomarkers for the
diagnosis of PJI.
Methods Synovial fluid was collected from 95 patients
meeting the inclusion criteria of this prospective diagnostic
study. All patients were being evaluated for a revision hip or
knee arthroplasty, including patients with systemic inflam-
matory disease and those already receiving antibiotic
treatment. The Musculoskeletal Infection Society (MSIS)
definition was used to classify 29 PJIs and 66 aseptic joints.
Synovial fluid samples were tested by immunoassay for 16
biomarkers optimized for use in synovial fluid. Sensitivity,
specificity, and receiver operating characteristic curve ana-
lysis were performed to assess for diagnostic performance.
Results Five biomarkers, including human a-defensin 1-3,
neutrophil elastase 2, bactericidal/permeability-increasing
protein, neutrophil gelatinase-associated lipocalin, and lac-
toferrin, correctly predicted the MSIS classification of all
patients in this study, with 100% sensitivity and specificity for
the diagnosis of PJI. An additional eight biomarkers demon-
strated excellent diagnostic strength, with an area under the
curve of greater than 0.9.
Conclusions Synovial fluid biomarkers exhibit a high
accuracy in diagnosing PJI, even when including patients with
systemic inflammatory disease and those receiving antibiotic
treatment.Considering that these biomarkers matchthe results
of the more complex MSIS definition of PJI, we believe that
synovial fluid biomarkers can be a valuable addition to the
methods utilized for the diagnosis of infection.
Level of Evidence Level II, diagnostic study. See
Instructions for Authors for a complete description of
levels of evidence.
The institution of one or more of the authors (CD, JP) has received,
during the study period, funding from CD Diagnostics (Wynnewood,
PA, USA) and Zimmer, Inc (Warsaw, IN, USA). Several of the
authors certify that they (KK, PK, KS, AC, JP), or a member of their
immediate family, have received or may receive payments or benefits,
during the study period, an amount of USD 10,000 to USD 100,000
from CD Diagnostics. One of the authors certifies that he (CD), or a
member of his or her immediate family, has received or may receive
payments or benefits, during the study period, an amount of more than
USD 1,000,001 from CD Diagnostics. One of the authors certifies that
he (JP), or a member of his or her immediate family, has received or
may receive payments or benefits, during the study period, an amount
of USD 100,001 to USD 1,000,000 from Zimmer, Inc. One of the
authors certifies that he (CD), or a member of his or her immediate
family, has received or may receive payments or benefits, during the
study period, an amount of USD 10,000 to USD 100,000 from
Zimmer, Inc.
All ICMJE Conflict of Interest Forms for authors and Clinical
Orthopaedics and Related Research
1
editors and board members are
on file with the publication and can be viewed on request.
Each author certifies that his or her institution approved the human
protocol for this investigation, that all investigations were conducted
in conformity with ethical principles of research, and that informed
consent for participation in the study was obtained when required.
This work was performed at CD Diagnostics Inc (Wynnewood, PA,
USA) and The Rothman Institute (Philadelphia, PA, USA).
C. Deirmengian (&), K. Kardos, P. Kilmartin, A. Cameron,
K. Schiller
CD Diagnostics Inc, Lankenau Institute for Medical Research,
100 Lancaster Avenue, MOB 456, Wynnewood, PA 19096, USA
e-mail: carl.deirmengian@rothmaninstitute.com
C. Deirmengian, J. Parvizi
The Rothman Institute, Thomas Jefferson University,
Philadelphia, PA, USA
123
Clin Orthop Relat Res
DOI 10.1007/s11999-014-3543-8
Clinical Orthopaedic
s
and Related Research
®
A Publication of
The Association of Bone and Joint Surgeons®
Introduction
Periprosthetic joint infection (PJI) accounts for 25% of failed
knee arthroplasties [6] and 15% of failed hip arthroplasties [7].
Concern regarding the predicted economic impact of PJI, due
to the increasing national volume of joint arthroplasties [13,
24] and increasing rate ofinfection [25,26], is well justified. In
caring for a painful joint arthroplasty, the ability to distinguish
between septic and aseptic failure of the prosthesis is critical,
as the treatment for PJI necessitates unique surgical strategies
that aim to eradicate the infecting organism(s) [15,32,40].
Currently, surgeons utilize a wide spectrum of tests in an
attempt to diagnose PJI, including (1) local measures of
synovial inflammation [3,12,18,38] (synovial fluid white
blood cell [WBC] count and differential, synovial tissue his-
tology), (2) systemic measures of inflammation [1,10,16]
(serum C-reactive protein [CRP] level, erythrocyte sedimen-
tation rate [ESR], IL-6), (3) radiographic tests [21,31,36,37]
(radiographs, bone scan, MRI, CT, positron emission
tomography), and (4) bacterial isolation techniques [2,17,27,
42] (Gram stain, culture). Facing the challenge of accurately
diagnosing PJI, the Musculoskeletal Infection Society (MSIS)
recently published a definition of PJI [33], utilizing a combi-
nation of clinical data and six of the above tests.
There is substantial evidence that there exists a primi-
tive, but specific, innate immune response to pathogens [9,
14,23,28,29,39]. In fact, the recognition of pathogens by
the innate immune system triggers a cascade of protective
pathways in the host. Microarray techniques have demon-
strated a unique gene expression signature exhibited by the
synovial fluid WBCs from infected joints, characteristic of
the innate host immune response to infection [9]. This
unique response to infection was also confirmed at the level
of the proteome, revealing several biomarkers that diag-
nostically outperformed the currently available tests for PJI
[8,22].
For more than 8 years, our group has been interested in the
discovery and evaluation of biomarkers for PJI [8,9,22], and
we have identified 16 biomarkers of interest. In this study, we
evaluated the diagnostic characteristics of these 16 promising
synovial fluid biomarkers for PJI.
Patients and Methods
Study Design
The study was approved by the institutional review board.
As part of a biomarker screening program initiated in 2009,
our institution archives and prospectively annotates synovial
fluid samples from the patients of adult arthroplasty sur-
geons. Patient inclusion in the current study required (1) an
evaluation for possible infection of a THA or TKA, (2)
sufficiently annotated clinical and laboratory data for clas-
sification by the MSIS criteria for PJI, and (3) sufficient
synovial fluid for study methods. We did not exclude from
this study patients receiving antibiotics before aspirations or
patients having the diagnosis of a systemic inflammatory
disease. Patients aspirated within 4 weeks after an index
procedure and patients with an adverse tissue reaction to
metal debris were excluded, as the MSIS definition for PJI
does not include specific considerations for these diagnoses.
We prospectively evaluated and classified patients with
PJI as defined by the MSIS [33] (Table 1). Although the
MSIS criteria were not specifically designed to rule out PJI
and PJI is acknowledged to potentially exist without meeting
the MSIS criteria, those patients not meeting the MSIS
criteria for PJI were, by default, classified as aseptic.
Additionally, sex, age, joint (hip/knee), surgical findings,
and isolated organism were recorded when pertinent. Sam-
ple size could not be calculated with any statistical rigor
given the novel biomarkers being evaluated. Therefore, we
chose to study a population of patients larger than those in
previously published studies [8,19,22]thathavedemon-
strated the diagnostic value of synovial fluid biomarkers.
Patients
Ninety-five patients met the criteria of the study; these
patients had 66 arthroplasties believed to be aseptic failures
and 29 arthroplasties diagnosed with PJI.
Patients classified as having an aseptic joint included 32 men
and 34 women, with a mean age of 67 years (range, 41–86
years). This group included nine hip arthroplasties, 55 knee
Table 1. MSIS Workgroup standard definition for PJI
One of the following must be met for diagnosis of PJI:
(1) A sinus tract communicating with the prosthesis
(2) A pathogen is isolated by culture from two separate tissue or fluid
samples obtained from the affected prosthetic joint
(3) Four of the following six criteria exist:
(a) Elevated ESR and CRP (ESR [30 mm/hour; CRP [10 mg/L)
(b) Elevated synovial fluid WBC count ([3000 cells/lL)
(c) Elevated synovial fluid neutrophil percentage ([65%)
(d) Presence of purulence in the affected joint
(e) Isolation of a microorganism in one periprosthetic tissue or fluid
culture
(f) [5 neutrophils per high-powered field in 5 high-power fields
observed from histologic analysis of periprosthetic tissue at 9400
magnification
MSIS = Musculoskeletal Infection Society; PJI = periprosthetic joint
infection; ESR = erythrocyte sedimentation rate; CRP = C-reactive
protein; WBC = white blood cell.
Deirmengian et al. Clinical Orthopaedics and Related Research
1
123
arthroplasties, and two knee cement spacers. The diagnoses
included 51 patients with aseptic loosening, three patients with
instability, two patients with bearing surface wear and well-
fixed implants, and 10 patients with pain but no mechanical
diagnosis. Eleven patients (17%) also had a diagnosis of sys-
temic inflammatory disease, including rheumatoid arthritis
(four), pseudogout (two), psoriasis (one), Crohn’s disease
(one), sarcoidosis (one), polymyalgia rheumatica (one), and
hepatitis C (one). Four patients (6%) were taking a medication
that modulates the immune system at the time of the diagnostic
aspiration. Three patients in the aseptic group had an isolated
positive culture that was considered a false positive, as the
MSIS minor criteria for PJI were not met. All three patients had
one isolated culture growing Staphylococcus epidermidis,two
in ‘‘broth only’’ and the third with ‘‘light growth’’ on solid
medium. All other preoperative and intraoperative cultures
from these patients (at least two additional for each patient)
were negative. No antibiotic treatments were provided to these
patients, as the surgeons considered the results to be false
positives. None of these patients had any other positive MSIS
minor criteria. Followup of 18 months, 4 months, and 4 months
revealed no further surgeries for these patients.
Patients classified as having PJI included 12 men and 17
women, with a mean age of 66 years (range, 49–89 years). This
group included two hip arthroplasties, 26 knee arthroplasties,
and one knee cement spacer. Among the 29 patients diagnosed
with PJI, 23 were culture positive and six were culture negative.
Organisms isolated included methicillin-sensitive Staphylo-
coccus aureus (six), methicillin-resistant S. aureus (four), S.
epidermidis (seven), Streptococcus mutans (one), Streptococ-
cus sanguinis (one), Streptococcus gordonii (one),
Corynebacterium striatum (one), Escherichia coli (one), and
Serratia marcescens (one). Eight patients with PJI (28%) also
had a diagnosis of systemic inflammatory disease, including
rheumatoid arthritis (three), chronic lymphocytic leukemia
(one), myelodysplastic syndrome (one), multiple sclerosis
(one), gout (one), and hepatitis C (one). Two patients (7%) were
taking a medication that modulates the immune system at the
time of the diagnostic aspiration. Six patients diagnosed with a
PJI (21%) were being treated with antibiotics at the time of
aspiration.
The relevant clinical and MSIS laboratory values for
patients with PJI versus those with aseptic disease are
shown (Table 2).
Sample Preparation and Biomarker Analysis
Synovial fluid was delivered to the laboratory immediately
after aspiration. Centrifugation was used to separate all
particulate and cellular material from each synovial fluid
sample, and the resulting supernatant was aliquoted and
frozen at 80°C.
Based on a review of our previous studies on biomarkers
for PJI [8,9,22], as well as the general literature on sepsis
biomarkers, we chose to screen 43 biomarkers that could
potentially be diagnostic for PJI (Table 3). These 43 bio-
markers were screened with a small subset of representative
aseptic and PJI samples to identify markers that demonstrated
an elevation in the setting of PJI. The 16 biomarkers evaluated
in this current study demonstrated the greatest and most
consistent elevations in the screening process: human
a-defensin 1–3 (a-defensin), IL-1a, IL-1, IL-6, IL-8, IL-10,
IL-17, granulocyte colony-stimulating factor (G-CSF), vas-
cular endothelial growth factor (VEGF), CRP, neutrophil
elastase 2 (ELA-2), lactoferrin, neutrophil gelatinase-associ-
ated lipocalin (NGAL), resistin, thrombospondin, and
bactericidal/permeability-increasing protein (BPI).
All immunoassays were optimized by laboratory scientists
with specific expertise in immunoassay development. Assays
were optimized to achieve an appropriate dynamic range and
minimize the sample matrix effect. Immunoassays for the
following synovial fluid biomarkers were generated using
reagents from EMD Millipore Corp (Billerica, MA, USA) and
measured using the bead-based platform from Luminex Corp
(Austin, TX, USA): IL-1a, IL-1, IL-6, IL-8, IL-10, IL-17,
G-CSF, VEGF, ELA-2, lactoferrin, NGAL, resistin, and
thrombospondin. Immunoassays for the following synovial
fluid biomarkers were generated using reagents from Hycult
Biotech (Uden, The Netherlands) and measured in duplicate
by standard ELISA: CRP, BPI, and a-defensin.
Data Analysis
The diagnostic performance of each test was assessed using
the MSIS definition as the gold standard. The diagnostic
value of each biomarker was evaluated by receiver operating
characteristic (ROC) curve analyses. The sensitivity and
specificity (and 95% CIs) of each synovial fluid biomarker
Table 2. MSIS relevant laboratory and clinical findings
Finding Aseptic group
(n = 66)
PJI group
(n = 29)
Sinus (number of patients) 0 4
At least one positive culture
(number of patients)
323
ESR (mm/hour)* 15 (11–20) 86 (71–107)
CRP (mg/L)* 4 (3–6) 122 (72–184)
SF WBC count (cells/lL)* 400 (300–655) 29,170 (10,755–47,000)
Neutrophil %* 13 (5–27) 89 (86–92)
* Values are expressed as median, with 95% CI in parentheses;
MSIS = Musculoskeletal Infection Society; PJI = periprosthetic joint
infection; ESR = erythrocyte sedimentation rate; CRP = C-reactive
protein; SF = synovial fluid; WBC = white blood cell.
Biomarkers for PJI Diagnosis
123
were calculated at various thresholds for a correct test result.
Test sensitivity was plotted against 1 specificity for every
tested threshold and the area under the curve (AUC) was
calculated. A test with an AUC value of greater than 0.9 is
considered to have excellent diagnostic strength, whereas an
AUC of 0.5 indicates a test with no diagnostic strength.
Optimum cutoff values for correspondence with the MSIS-
defined diagnosis were determined by Youden’s J statistic.
For purposes of ROC analysis, raw data were processed
according to the following rules: (1) the lowest reportable
value was used for any samples that had a concentration
below the limit of detection for an assay and (2) samples with
results above the measuring range of an assay were diluted
into range and corrected for dilution.
For samples with the diagnosis of infection, we compared
the concentrations of select biomarkers to the synovial fluid
WBC count and to each other by Pearson correlation. The
following descriptions were utilized: r[0.6 = strong positive
relationship, +0.40 \r\+0.59 = moderate positive rela-
tionship, +0.19 \r\+0.39 = weak positive relationship,
+0.20[r[0.19 = no relationship, 0.20[r[0.39 =
weak negative relationship, 0.40 [r[0.59 = moderate
negative relationship, and r \0.60 = strong negative
relationship.
For all statistical analyses, we used GraphPad Prism
1
software (Version 6; GraphPad Software Inc, San Diego,
CA, USA).
Results
Five biomarkers (a-defensin, ELA-2, BPI, NGAL, and
lactoferrin) correctly predicted the diagnosis as defined by
the MSIS criteria for every patient in the study. These
biomarkers had a sensitivity of 100% (95% CI: 88%–
100%) and a specificity of 100% (95% CI: 94%–100%)
(Table 4). The AUC values for these five biomarkers were
1.000. An additional eight biomarkers (IL-8, CRP, resistin,
thrombospondin, IL-1b, IL-6, IL-10, and IL-1a) demon-
strated AUC values of greater than 0.9.
We further evaluated the five biomarkers demonstrating
100% sensitivity and specificity for PJI. Dot plots of these
biomarkers compare the diagnostic separation of the
aseptic and septic groups using median values and inter-
quartile ranges (Fig. 1). For comparison, dot plots are also
provided comparing the diagnostic separation of the aseptic
and septic groups for ESR, serum CRP, synovial fluid
WBC count, and neutrophil percentage (Fig. 2).
The five biomarkers demonstrating 100% sensitivity
and specificity were compared to each other and to the
synovial fluid WBC count using the Pearson correlation
to evaluate for redundant performance among infected
samples (Table 5). The mean correlation between bio-
markers and the synovial fluid WBC count was 0.12
(range, 0.02 to 0.364), demonstrating no correlation.
The biomarkers and synovial fluid WBC count had
predominantly weak or no correlations with each other
among samples with PJI.
There were no statistically significant differences
between subgroups of patients in this study (systemic
inflammatory disease versus other; antibiotic treatment
versus other) in regard to mean ESR, CRP, synovial fluid
WBC count, or biomarker.
Table 3. Forty-three biomarkers initially screened for inclusion in
this study
Proteins passing screen (n = 16) Proteins failing screen (n = 27)
Human a-defensin 1-3 Procalcitonin
Interleukin 1aTransforming growth factor a
Interleukin 1bCathelicidin (LL-37)
Interleukin 6 Lipopolysaccharide binding protein
Interleukin 8 Calcitonin gene-related peptide
Interleukin 10 Orsomucoid
Interleukin 17 Nibrin
Granulocyte colony-stimulating
factor
Tumor necrosis factor-stimulated
gene 6 protein
Vascular endothelial growth
factor
Plekstrin
C-reactive protein Superoxide dismutase 2
Neutrophil elastase 2 Urokinase
Lactoferrin Migration inhibitory factor
Neutrophil gelatinase-
associated lipocalin
Plasminogen activator inhibitor
type 1
Resistin Soluble Fas
Thrombospondin 1 Soluble Fas ligand
Bactericidal/permeability-
increasing protein
Soluble intercellular adhesion
molecule 1
Soluble vascular cell adhesion
molecule 1
Granzyme B
Heat shock protein 70
Macrophage inflammatory
protein 1a
Macrophage inflammatory
protein 1b
Matrix metalloproteinase 8
Tumor necrosis factor a
Interferon-cinducible protein
Fibroblast growth factor 2
a-2 macroglobulin
Skin-derived antileukoprotease
Deirmengian et al. Clinical Orthopaedics and Related Research
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123
Discussion
The diagnosis of PJI has challenged surgeons since the
advent of joint arthroplasty. There are several reasons for
this diagnostic difficulty, including the absence of specific
clinical signs and symptoms, the relative lack of accurate
laboratory tests [20,30,32], and difficulties in culture
isolation of pathogens due to prior therapy and formation
of biofilms. The MSIS recently responded to this diagnostic
difficulty by developing a definition for PJI [33]. As with
any criteria-based tool, there are some practical clinical
difficulties in using the MSIS definition for PJI, including
(1) the subjective nature of several criteria, including the
observation of purulence and interpretation of the frozen-
section histology; (2) the delay in diagnosis required by
waiting for several independent culture results; and (3) the
relative complexity of the definition. A laboratory diag-
nostic test for PJI that provides a diagnosis matching the
MSIS criteria would be highly desirable. Therefore, we
evaluated the diagnostic characteristics of 16 promising
synovial fluid biomarkers for PJI.
There are several weaknesses of this study. First, this
study chose cutoff values to provide for the optimal per-
formance of the biomarkers in this group of patients. Future
studies may demonstrate a decline in performance when
validating the cutoffs chosen in this study. Second, we
excluded patients in the immediate postoperative period
and those with suspected hip metallosis due to concerns
that the MSIS criteria used in this study may not apply to
these groups. Additionally, the subgroups of patients with
cement spacers or systemic inflammatory disease were
small. Therefore, it may not be valid to widely apply our
results to these smaller subgroups until future studies with
larger numbers are completed. Third, any diagnostic study
is somewhat limited by the assumption that its patient
population and prevalence of disease are similar to the
more general population of such patients. The prevalence
of PJI in this study was 31%, which is similar to the
prevalence of PJI in a recent meta-analysis of 3909 patients
tested for PJI (32.5%) [5]. In addition, we used sensitivity
and specificity as the descriptive diagnostic measures in
this study, which would not be affected by the prevalence
of PJI in this study. As a final weakness, we included a
heterogeneous group of patients in the aseptic disease
group in an attempt to accurately represent the population
of patients tested in clinical practice. These included
patients with instability, patients with polyethylene wear,
and patients with pain in the absence of an objective
mechanical complication. The prevalence of diseases in the
aseptic group could have hypothetically affected the
specificity of our results. However, given the fact that
many of the biomarkers exhibited 100% sensitivity and
specificity for PJI, the decision to exclude patients with
diagnoses other than aseptic loosening would not have
substantially changed our results.
In this study, we evaluated 16 biomarkers for PJI based
on nearly a decade of pursuit for optimal performance. Five
biomarkers in the study provided a diagnosis that matched
Table 4. Diagnostic characteristics of synovial fluid biomarkers
Biomarker AUC Cutoff Specificity (%) 95% CI (%) Sensitivity (%) 95% CI (%)
a-Defensin 1.000 4.8 lg/mL 100 95–100 100 88–100
ELA-2 1.000 2.0 lg/mL 100 95–100 100 88–100
BPI 1.000 2.2 lg/mL 100 95–100 100 88–100
NGAL 1.000 2.2 lg/mL 100 95–100 100 88–100
Lactoferrin 1.000 7.5 lg/mL 100 95–100 100 88–100
IL-8 0.992 6.5 ng/mL 95 87–99 100 87–100
SF CRP 0.987 12.2 mg/L 97 90–100 90 73–98
Resistin 0.983 340 ng/mL 100 95–100 97 82–99
Thrombospondin 0.974 1061 ng/mL 97 90–100 90 73–98
IL-1b0.966 3.1 pg/mL 95 87–99 96 82–100
IL-6 0.950 2.3 ng/mL 97 89–100 89 71–98
IL-10 0.930 32.0 pg/mL 89 79–96 89 72–98
IL-1a0.922 4.0 pg/mL 91 81–97 82 63–94
IL-17 0.892 3.1 pg/mL 99 92–100 82 63–94
G-CSF 0.859 15.4 pg/mL 92. 82–97 82 62–94
VEGF 0.850 2.3 ng/mL 77 65–87 75 55–89
AUC = area under the curve; a-defensin = human a-defensin 1-3; ELA-2 = neutrophil elastase 2; BPI = bactericidal/permeability-increasing
protein; NGAL = neutrophil gelatinase-associated lipocalin; SF = synovial fluid; CRP = C-reactive protein; G-CSF = granulocyte colony-
stimulating factor; VEGF = vascular endothelial growth factor.
Biomarkers for PJI Diagnosis
123
that of the MSIS definition for all 95 patients in this study,
with 100% sensitivity and specificity. Eight additional
biomarkers were identified with AUC values of greater
than 0.9, exhibiting excellent diagnostic strength for PJI.
Obviously, no test is perfect, and future studies with more
patients, or those focusing on subgroups of patients, may
demonstrate a decline in these results. Nevertheless, these
biomarkers outperform historical reports of the currently
used diagnostic tests for PJI, including serum CRP [2,16,
20,34], ESR [2,16,20,34], and synovial fluid WBC count
and differential [18,35,41], despite the inclusion of a more
challenging group of patients.
The promise of synovial fluid biomarkers to diagnose
PJI has been previously reported [8,19,22]. Similar to
these previous studies, we found that cytokines and pro-
teins with antimicrobial function provide the greatest utility
for diagnosing PJI. To our knowledge, this study is the first
to describe the performance of synovial fluid a-defensin,
ELA-2, BPI, NGAL, and lactoferrin for the diagnosis of
PJI. These biomarkers are all host proteins with direct
antimicrobial activity, playing important roles in the innate
response to eliminate pathogens [4,11]. When pathogens
are present, these biomarkers become more concentrated in
the synovial fluid. Therefore, it is no surprise that these
proteins are found to be diagnostically important for PJI.
If the biomarkers described in this study were merely
mirroring the state of inflammation, we would have
expected strong correlations among the biomarkers and
between the biomarkers and synovial fluid WBC count.
However, we did not identify many strong correlations
between biomarkers and synovial fluid WBC count among
infected patients. Nor did we identify many strong corre-
lations among differing biomarkers. Therefore, it appears
that these biomarkers are not merely redundant proxies for
Fig. 1A–E Log-scale dot plots
demonstrate the diagnostic sep-
aration of study groups achieved
by the five biomarkers achiev-
ing 100% sensitivity and
specificity: (A) a-defensin,
(B) ELA-2, (C) BPI, (D) lacto-
ferrin, and (E) NGAL. The
lowest reportable value was
used for any samples that had
a concentration below the limit
of detection for each assay.
Horizontal line = median; bars =
interquartile range.
Deirmengian et al. Clinical Orthopaedics and Related Research
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123
the local level of inflammation but instead are being
modulated by other underlying causes.
There are several strengths of this study. First, to our
knowledge, this is one of the largest diagnostic studies to
date that utilizes the rigorous gold-standard MSIS defini-
tion for PJI. Second, patients usually excluded from similar
diagnostic studies, such as those on antibiotics and those
with systemic inflammatory disease, were included in this
study to emulate standard clinical practice. In fact, 21% of
infected patients in this study were on antibiotic treatment
at the time of synovial fluid aspiration and 20% of all
patients in the study had a history of systemic inflammatory
disease, resulting in a historically challenging patient
population. Finally, while some diagnostic biomarker
studies limit their samples of PJI to a single organism [9,
19], our study included all infected patients diagnosed by
the MSIS criteria, demonstrating utility of the biomarkers
for most representative pathogens. Based on this study,
which supports our earlier work [8,9,22], we conclude that
synovial fluid biomarkers show promise as a valuable tool
for the diagnosis of PJI. Given the ability of these assays to
match the results of the more complex MSIS definition of
PJI, we believe that these assays can improve the diag-
nostic accuracy in the field.
Acknowledgments We acknowledge Dana Geiser (Rothman Insti-
tute), Kyle Birkmeyer (CD Diagnostics), and Gregory Kazarian (CD
Diagnostics) for their efforts in sample collection and data acquisition
for this study.
Fig. 2A–D Log-scale dot plots
demonstrate the diagnostic sep-
aration of study groups achieved
by traditional tests for PJI:
(A) ESR, (B) serum CRP,
(C) neutrophil percentage, and
(D) synovial fluid WBC count.
Horizontal bar = median; error
bars = interquartile range.
Table 5. Pearson correlations with degree and type of correlation among patients with PJI
Biomarker r value
a-Defensin BPI ELA-2 Lactoferrin NGAL
a-Defensin
BPI 0.40 (moderate +)
ELA-2 0.25 (weak +) 0.22 (weak +)
Lactoferrin 0.06 (none) 0.14 (none) 0.50 (moderate +)
NGAL 0.23 (weak +) 0.44 (moderate +) 0.50 (moderate +) 0.75 (strong +)
SF WBC count 0.08 (none) 0.12 (none) 0.02 (none) 0.31 (weak +) 0.36 (weak +)
PJI = periprosthetic joint infection; a-defensin = human a-defensin 1-3; BPI = bactericidal/permeability-increasing protein; ELA-2 = neutrophil
elastase 2; NGAL = neutrophil gelatinase-associated lipocalin; SF = synovial fluid; WBC = white blood cell; += positive.
Biomarkers for PJI Diagnosis
123
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tribution, and reproduction in any medium, provided the original
author(s) and the source are credited.
References
1. Austin MS, Ghanem E, Joshi A, Lindsay A, Parvizi J. A simple,
cost-effective screening protocol to rule out periprosthetic
infection. J Arthroplasty. 2008;23:65–68.
2. Bare J, MacDonald SJ, Bourne RB. Preoperative evaluations in
revision total knee arthroplasty. Clin Orthop Relat Res.
2006;446:40–44.
3. Bedair H, Ting N, Jacovides C, Saxena A, Moric M, Parvizi J,
Della Valle CJ. The Mark Coventry Award. Diagnosis of early
postoperative TKA infection using synovial fluid analysis. Clin
Orthop Relat Res. 2011;469:34–40.
4. Belaaouaj A, McCarthy R, Baumann M, Gao Z, Ley TJ, Abraham
SN, Shapiro SD. Mice lacking neutrophil elastase reveal impaired
host defense against gram negative bacterial sepsis. Nat Med.
1998;4:615–618.
5. Berbari E, Mabry T, Tsaras G, Spangehl M, Erwin PJ, Murad
MH, Steckelberg J, Osmon D. Inflammatory blood laboratory
levels as markers of prosthetic joint infection: a systematic
review and meta-analysis. J Bone Joint Surg Am. 2010;92:
2102–2109.
6. Bozic KJ, Kurtz SM, Lau E, Ong K, Chiu V, Vail TP, Rubash HE,
Berry DJ. The epidemiology of revision total knee arthroplasty in
the United States. Clin Orthop Relat Res. 2010;468:45–51.
7. Bozic KJ, Kurtz SM, Lau E, Ong K, Vail TP, Berry DJ. The
epidemiology of revision total hip arthroplasty in the United
States. J Bone Joint Surg Am. 2009;91:128–133.
8. Deirmengian C, Hallab N, Tarabishy A, Della Valle C, Jacobs JJ,
Lonner J, Booth RE Jr. Synovial fluid biomarkers for peripros-
thetic infection. Clin Orthop Relat Res. 2010;468:2017–2023.
9. Deirmengian C, Lonner JH, Booth RE Jr. The Mark Coventry
Award. White blood cell gene expression: a new approach toward
the study and diagnosis of infection. Clin Orthop Relat Res.
2005;440:38–44.
10. Della Valle CJ, Sporer SM, Jacobs JJ, Berger RA, Rosenberg AG,
Paprosky WG. Preoperative testing for sepsis before revision total
knee arthroplasty. J Arthroplasty. 2007;22:90–93.
11. Diamond G, Beckloff N, Weinberg A, Kisich KO. The roles of
antimicrobial peptides in innate host defense. Curr Pharm Des.
2009;15:2377–2392.
12. Fehring TK, McAlister JA Jr. Frozen histologic section as a guide
to sepsis in revision joint arthroplasty. Clin Orthop Relat Res.
1994:229–237.
13. Fehring TK, Odum SM, Troyer JL, Iorio R, Kurtz SM, Lau EC.
Joint replacement access in 2016: a supply side crisis. J Arthro-
plasty. 2010;25:1175–1181.
14. Fessler MB, Malcolm KC, Duncan MW, Worthen GS. A geno-
mic and proteomic analysis of activation of the human neutrophil
by lipopolysaccharide and its mediation by p38 mitogen-acti-
vated protein kinase. J Biol Chem. 2002;277:31291–31302.
15. Garvin KL, Konigsberg BS. Infection following total knee
arthroplasty: prevention and management. Instr Course Lect.
2012;61:411–419.
16. Ghanem E, Antoci V Jr, Pulido L, Joshi A, Hozack W, Parvizi J.
The use of receiver operating characteristics analysis in deter-
mining erythrocyte sedimentation rate and C-reactive protein
levels in diagnosing periprosthetic infection prior to revision total
hip arthroplasty. Int J Infect Dis. 2009;13:e444–e449.
17. Ghanem E, Ketonis C, Restrepo C, Joshi A, Barrack R, Parvizi J.
Periprosthetic infection: where do we stand with regard to Gram
stain? Acta Orthop. 2009;80:37–40.
18. Ghanem E, Parvizi J, Burnett RS, Sharkey PF, Keshavarzi N,
Aggarwal A, Barrack RL. Cell count and differential of aspirated
fluid in the diagnosis of infection at the site of total knee
arthroplasty. J Bone Joint Surg Am. 2008;90:1637–1643.
19. Gollwitzer H, Dombrowski Y, Prodinger PM, Peric M, Summer
B, Hapfelmeier A, Saldamli B, Pankow F, von Eisenhart-Rothe
R, Imhoff AB, Schauber J, Thomas P, Burgkart R, Banke IJ.
Antimicrobial peptides and proinflammatory cytokines in peri-
prosthetic joint infection. J Bone Joint Surg Am. 2013;95:
644–651.
20. Greidanus NV, Masri BA, Garbuz DS, Wilson SD, McAlinden
MG, Xu M, Duncan CP. Use of erythrocyte sedimentation rate
and C-reactive protein level to diagnose infection before revision
total knee arthroplasty; a prospective evaluation. J Bone Joint
Surg Am. 2007;89:1409–1416.
21. Hayter CL, Koff MF, Potter HG. Magnetic resonance imaging of
the postoperative hip. J Magn Reson Imaging. 2012;35:1013–
1025.
22. Jacovides CL, Parvizi J, Adeli B, Jung KA. Molecular markers
for diagnosis of periprosthetic joint infection. J Arthroplasty.
2011;26(6 suppl):99–103.e1.
23. Kim SA, Yoo SM, Hyun SH, Choi CH, Yang SY, Kim HJ, Jang BC,
Suh SI, Lee JC. Global gene expression patterns and induction of
innate immune response in human laryngeal epithelial cells in
response to Acinetobacter baumannii outer membrane protein A.
FEMS Immunol Med Microbiol. 2008;54:45–52.
24. Kurtz S, Ong K, Lau E, Mowat F, Halpern M. Projections of
primary and revision hip and knee arthroplasty in the United
States from 2005 to 2030. J Bone Joint Surg Am. 2007;89:
780–785.
25. Kurtz SM, Lau E, Schmier J, Ong KL, Zhao K, Parvizi J.
Infection burden for hip and knee arthroplasty in the United
States. J Arthroplasty. 2008;23:984–991.
26. Kurtz SM, Lau E, Watson H, Schmier JK, Parvizi J. Economic
burden of periprosthetic joint infection in the United States. J
Arthroplasty. 2012;27(8 suppl):61–65.e1.
27. Malekzadeh D, Osmon DR, Lahr BD, Hanssen AD, Berbari EF.
Prior use of antimicrobial therapy is a risk factor for culture-
negative prosthetic joint infection. Clin Orthop Relat Res.
2010;468:2039–2045.
28. Manger ID, Relman DA. How the host ‘‘sees’’ pathogens: global
gene expression responses to infection. Curr Opin Immunol.
2000;12:215–218.
29. Matussek A, Strindhall J, Stark L, Rohde M, Geffers R, Buer J,
Kihlstrom E, Lindgren PE, Lofgren S. Infection of human
endothelial cells with Staphylococcus aureus induces transcrip-
tion of genes encoding an innate immunity response. Scand J
Immunol. 2005;61:536–544.
30. Morgan PM, Sharkey P, Ghanem E, Parvizi J, Clohisy JC,
Burnett RS, Barrack RL. The value of intraoperative Gram stain
in revision total knee arthroplasty. J Bone Joint Surg Am.
2009;91:2124–2129.
31. Nagoya S, Kaya M, Sasaki M, Tateda K, Yamashita T. Diagnosis
of peri-prosthetic infection at the hip using triple-phase bone
scintigraphy. J Bone Joint Surg Br. 2008;90:140–144.
32. Parvizi J, Adeli B, Zmistowski B, Restrepo C, Greenwald AS.
Management of periprostheticjoint infection:the current knowledge:
AAOS exhibit selection. J Bone Joint Surg Am. 2012;94:e104.
33. Parvizi J, Zmistowski B, Berbari EF, Bauer TW, Springer BD,
Della Valle CJ, Garvin KL, Mont MA, Wongworawat MD,
Zalavras CG. New definition for periprosthetic joint infection:
from the Workgroup of the Musculoskeletal Infection Society.
Clin Orthop Relat Res. 2011;469:2992–2994.
Deirmengian et al. Clinical Orthopaedics and Related Research
1
123
34. Piper KE, Fernandez-Sampedro M, Steckelberg KE, Mandrekar
JN, Karau MJ, Steckelberg JM, Berbari EF, Osmon DR, Hanssen
AD, Lewallen DG, Cofield RH, Sperling JW, Sanchez-Sotelo J,
Huddleston PM, Dekutoski MB, Yaszemski M, Currier B, Patel
R. C-reactive protein, erythrocyte sedimentation rate and ortho-
pedic implant infection. PloS One. 2010;5:e9358.
35. Schinsky MF, Della Valle CJ, Sporer SM, Paprosky WG.
Perioperative testing for joint infection in patients undergoing
revision total hip arthroplasty. J Bone Joint Surg Am.
2008;90:1869–1875.
36. Simonsen L, Buhl A, Oersnes T, Duus B. White blood cell
scintigraphy for differentiation of infection and aseptic loosening:
a retrospective study of 76 painful hip prostheses. Acta Orthop.
2007;78:640–647.
37. Sofka CM, Potter HG, Adler RS, Pavlov H. Musculoskeletal
imaging update: current applications of advanced imaging tech-
niques to evaluate the early and long-term complications of
patients with orthopedic implants. HSS J. 2006;2:73–77.
38. Tsaras G, Maduka-Ezeh A, Inwards CY, Mabry T, Erwin PJ,
Murad MH, Montori VM, West CP, Osmon DR, Berbari EF.
Utility of intraoperative frozen section histopathology in the
diagnosis of periprosthetic joint infection: a systematic review
and meta-analysis. J Bone Joint Surg Am. 2012;94:1700–1711.
39. Tzou P, De Gregorio E, Lemaitre B. How Drosophila combats
microbial infection: a model to study innate immunity and host-
pathogen interactions. Curr Opin Microbiol. 2002;5:102–110.
40. Wolf CF, Gu NY, Doctor JN, Manner PA, Leopold SS. Com-
parison of one and two-stage revision of total hip arthroplasty
complicated by infection: a Markov expected-utility decision
analysis. J Bone Joint Surg Am. 2011;93:631–639.
41. Zmistowski B, Restrepo C, Huang R, Hozack WJ, Parvizi J. Peri-
prosthetic joint infection diagnosis: a complete understanding of white
blood cell count and differential. JArthroplasty.2012;27:1589–1593.
42. Zywiel MG, Stroh DA, Johnson AJ, Marker DR, Mont MA.
Gram stains have limited application in the diagnosis of infected
total knee arthroplasty. Int J Infect Dis. 2011;15:e702–e705.
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