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Inflammatory Blood Laboratory Levels as Markers of Prosthetic Joint InfectionA Systematic Review and Meta-Analysis
Elie Berbari, MD1; Tad Mabry, MD1; Geoffrey Tsaras, MD1; Mark Spangehl, MD2; Pat J. Erwin, MLS1; Mohammad Hassan Murad, MD1; James Steckelberg, MD1; Douglas Osmon, MD1
1 Section of Orthopedic Infectious Diseases (E.B., G.T., J.S., and D.O.), Departments of Orthopedic Surgery (T.M.) and Medical Education (P.J.E.), and Knowledge and Encounter Research Unit (M.H.M.), Mayo Clinic College of Medicine, 200 First Street S.W., Rochester, MN 55905. E-mail address for E. Berbari: berbari.elie@mayo.edu
2 Department of Orthopedic Surgery, Mayo Clinic College of Medicine, 5777 East Mayo Boulevard, Phoenix, AZ 85054
View Disclosures and Other Information
Disclosure: The authors did not receive any outside funding or grants in support of their research for or preparation of this work. Neither they nor a member of their immediate families received payments or other benefits or a commitment or agreement to provide such benefits from a commercial entity.

Investigation performed at Mayo Clinic College of Medicine, Rochester, Minnesota

Copyright © 2010 by The Journal of Bone and Joint Surgery, Inc.
J Bone Joint Surg Am, 2010 Sep 01;92(11):2102-2109. doi: 10.2106/JBJS.I.01199
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Abstract

Background: 

The preoperative diagnosis of prosthetic joint infection in patients with a total hip or knee arthroplasty may rely in part on the use of systemic inflammation markers. These markers have unclear accuracy. The objective of this review was to summarize the evidence on the accuracy of the peripheral white blood-cell count, the erythrocyte sedimentation rate, serum C-reactive protein levels, and serum interleukin-6 levels for the diagnosis of prosthetic joint infection.

Methods: 

We searched electronic databases (MEDLINE, EMBASE, Cochrane Library, Web of Science, and Scopus) from 1950 through 2009. Eligible studies evaluated the accuracy of white blood-cell count, erythrocyte sedimentation rate, serum C-reactive protein level, and serum interleukin-6 level for the intraoperative diagnosis of prosthetic joint infection at the time of revision arthroplasty. Two reviewers working independently extracted study characteristics and data to estimate the diagnostic odds ratio and 95% confidence interval for each result.

Results: 

We included thirty eligible studies that included 3909 revision total hip or knee arthroplasties. The prevalence of prosthetic joint infection was 32.5% (1270 of 3909). The accuracy of assessed inflammation markers, represented with a diagnostic odds ratio, was 314.7 (95% confidence interval, 113.0 to 876.8) for interleukin-6 (three studies), 13.1 (95% confidence interval, 7.9 to 21.7) for C-reactive protein level (twenty-three studies), 7.2 (95% confidence interval, 4.7 to 10.9) for erythrocyte sedimentation rate (twenty-five studies), and 4.4 (95% confidence interval, 2.9 to 6.6) for white blood-cell count (fifteen studies).

Conclusions: 

The diagnostic accuracy for prosthetic joint infection was best for interleukin-6, followed by C-reactive protein level, erythrocyte sedimentation rate, and white blood-cell count. Given the limited numbers of studies assessing interleukin-6 levels, further investigations assessing the accuracy of interleukin-6 for the diagnosis of prosthetic joint infection are warranted.

Level of Evidence: 

Diagnostic Level II. See Instructions to Authors for a complete description of levels of evidence.

Figures in this Article
    Establishing a definitive diagnosis of prosthetic joint infection prior to surgical intervention is at times difficult. Signs and symptoms of infection such as fever, chills, or elevated peripheral white blood-cell count are often lacking in patients with prosthetic joint infection. More specific clinical signs such as fever or the presence of a sinus tract are often absent, making these clinical variables insensitive. Joint pain, often present in these patients, also can be due to a variety of noninfectious conditions, such as aseptic loosening, mechanical instability, prosthesis malalignment, or crystal-induced arthropathy. The erythrocyte sedimentation rate (ESR) and white blood-cell (WBC) count reportedly have relatively low sensitivity and specificity as markers of prosthetic joint infection1. Newer markers such as the C-reactive protein (CRP) and interleukin-6 (IL-6) levels have been recently assessed2-4. Although these newer markers seem to have better accuracy, their diagnostic utility has not been clearly established. The purpose of the present study was to calculate and summarize the diagnostic accuracy of four of these markers with respect to prosthetic joint infection.
    A protocol that had been written before this review was undertaken as recommended by the Quality of Reporting of Meta-analyses (QUOROM) statement5.

    Search Strategy and Identification of Studies

    All studies indexed in Ovid MEDLINE, Ovid EMBASE, the Cochrane Library, ISI Web of Science, and Scopus databases from 1950 or inception until January 31, 2009, that evaluated white blood-cell count, erythrocyte sedimentation rate, C-reactive protein level, and interleukin-6 as markers for total hip or total knee arthroplasty infection were identified. With the use of Boolean strategy, textword and subject headings included (1) type of prosthesis (joint prosthesis or arthroplasty, specific joint-associated procedures) and (exp hip joint/ or exp knee joint/ or hip.mp. or knee) and (2) the various markers (CRP, ESR, WBC, and IL-6), both as textwords and as subject headings. The bibliographies of relevant articles were further cross-checked to search for articles not referenced in the search. Studies of patients from all age groups that evaluated the use of markers prior to suspected prosthetic joint infection were evaluated. The selection of articles was performed by two authors (E.B. and T.M.). Raw data from the articles were used to reconstruct 2 × 2 tables (see data-extraction paragraph below). When not provided in the original article, the tables were reconstructed by using the reported sensitivity and specificity as well as the prevalence of prosthetic joint infection in the cohort and the total number of patients studied. When only summary qualitative values were reported, the authors of the original article were contacted by e-mail in order to obtain data allowing us to reconstruct the 2 × 2 tables. Two of the authors of the present study (D.O. and M.S.) were asked to review the current list of included papers and to conduct their own search. With use of this recapture strategy, no additional relevant publications were identified.

    Eligibility Criteria

    We included cross-sectional and longitudinal studies that enrolled participants with true diagnostic uncertainty. Tests of interest were blood or serum measurement of the white blood-cell count, C-reactive protein level, interleukin-6 level, and erythrocyte sedimentation rate. Eligible studies had a reference standard for diagnosing prosthetic joint infection and calculated the accuracy of inflammation markers test results, with results expressed (1) as both sensitivity and specificity or (2) as a likelihood ratio. We included studies regardless of their publication status, language, or size.

    Quality Assessment

    Two reviewers (E.B. and G.T.) working independently and in duplicate analyzed the included articles to assess the reported quality of the methods with use of the tool for quality assessment of studies of diagnostic accuracy included in systematic reviews (QUADAS)6. All authors were contacted to obtain their response to the QUADAS questions. When responses were different from the author's assessment, the paper was reviewed and a consensus answer was derived. As there is not a widely accepted standard and validated definition of prosthetic joint infection, five of the authors (E.B., T.M., J.S., D.O., and M.S.), all experts in the field, agreed on the following grading system for the definition of prosthetic joint infection, with use of a consensus process: (1) two or more periprosthetic cultures showing growth of the same organisms, or the presence of a sinus tract communicating with the prosthesis (best), or (2) presence of acute inflammation on histopathologic examination of periprosthetic tissue or the presence of purulence in the periprosthetic space (good), or (3) any other definition loosely based on culture or operative findings but not further specified (mediocre).

    Data Extraction

    Three reviewers (E.B., G.T., and T.M.), working independently, used a standardized form to extract descriptions of study participants, including the diagnostic tests performed, the cutoff or range definitions of the tests, whether the cutoff values were derived with use of receiver operator characteristic curves or were predetermined by the study authors, and the nature and characteristics of the reference standard used. To extract data for the estimation of diagnostic accuracy measures, we used the cutoff values that the authors chose to use in the primary studies. If more than one cutoff was reported or if the results were reported at the individual patient level, then we used cutoff values that offered the best test performance.

    Author Contact

    We sent letters to the corresponding authors (or any other author with a contact address listed on the main manuscript) of each of the eligible studies by e-mail (or by regular mail if we could not obtain an active e-mail address). We asked the authors to verify the data that we had extracted and to complete missing data.

    Statistical Analysis

    We used Meta-DiSc Software for Meta-analysis for Diagnostic and Screening tests (version 1.4)7. We pooled, using random effects meta-analyses, the sensitivities, specificities, likelihood ratios, and diagnostic odds ratios and estimated the 95% confidence intervals for the outcomes. Because of the interrelation between the pooled sensitivity and specificity, we focused the analysis on estimating and pooling likelihood ratios and diagnostic odds ratios. The likelihood ratio incorporates both the sensitivity and specificity and provides an estimate of how much a test result will change the odds of having a disease. In this case, the likelihood ratio for a positive result indicates how much the odds of prosthetic joint infection increase when a test is positive. The likelihood ratio for a negative result indicates how much the odds of prosthetic joint infection decrease when a test is negative.
    To simplify comparison across tests, both the likelihood ratio for a positive result and the likelihood ratio for a negative result are incorporated in the diagnostic odds ratio, which provides a global estimate of agreement between a test and a reference standard. The higher the diagnostic odds ratio, the higher accuracy a test has8. Therefore, the diagnostic odds ratio allows pooling across studies when the main source of inconsistency is the threshold to consider a test positive (i.e., when there is a common receiver operator characteristic curve across all studies)9.
    Summary receiver operator characteristic curves depict the consistency of results across studies (answering the question of whether there is a single receiver operator characteristic curve across all of these studies) and the accuracy of the test, as judged by the area under the summary receiver operator characteristic curve. The summary receiver operator characteristic graph is conceptually very similar to the receiver operator characteristic curve. However, each data point comes from a different study, not a different threshold. It is calculated by using a regression model and placing it over the points to form a smooth curve. Like a receiver operator characteristic curve, the summary receiver operator characteristic curve is plotted over the original points (sensitivity, 1 — specificity) on the original axes. The Q value is estimated to reflect the overall accuracy of summary receiver operator characteristic analyses. It is calculated on the basis of the intersection of the summary receiver operator characteristic curve and the antidiagonal line of the square. Its value correlates with the area under the curve. The closer the curve is to the top left corner, the better the accuracy is, and the higher the Q value.
    The inconsistency among studies was assessed with use of the I2 statistic, which represents the proportion of variability across studies that is not due to chance or random error. For example, an I2 value of 30% indicates that 30% of the variability in study results is due to differences in patient populations or study protocols, whereas the remaining variability (70%) is expected to be due to random sampling error. Traditionally, I2 values of 25%, 50%, and 75% indicate low, moderate, and high heterogeneity, respectively10.

    Subgroup Analyses

    A priori hypotheses to explain potential heterogeneity among studies included the site of the prosthesis (hip versus knee), cutoff rationale (receiver operator characteristic-derived versus preestablished cutoff), whether the spectrum of patients was representative (yes versus no), and definition of prosthetic joint infection (best versus good and mediocre). We tested these hypotheses with use of a test for interaction, with the level of significance set at p < 0.05.

    Source of Funding

    There was no external source of funding for this study.

    Search Results

    Our initial search yielded 327 publications. Of these, forty-nine studies were determined to be of interest and were retrieved in full text. Thirty articles that evaluated the blood markers of interest prior to surgical intervention in patients suspected of having either prosthetic hip or knee infection were identified and were included in this review (Fig. 1)1-4,11-36. No additional articles were found by searching the bibliographies of selected articles or by the independent search performed by two of the authors. A table in the Appendix lists the included studies and describes these baseline characteristics. A total of 3909 revision arthroplasties were identified. Fifty-one percent of the revisions were total hip arthroplasties (1966 of 3851), and 49% were total knee arthroplasties (1885 of 3851). (In one study24, the numbers of total hip and total knee arthroplasties were not reported individually and were not included.) The prevalence of prosthetic joint infection was 32.5% (1270 of 3909).
     
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    Flow chart illustrating the identification of articles that were eligible for inclusion in the systematic review. WBC = white blood-cell count, ESR = erythrocyte sedimentation rate, CRP = C-reactive protein level, IL-6 = interleukin-6.

    Figure Description

    Quality Assessment

    The methodological evaluation of study quality with use of the QUADAS, a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews, is presented in a table in the Appendix. The median QUADAS cumulative score of the twelve yes-no questions for the included studies was 9 yes answers (25% to 75% interquartile range, 6 to 10). The questionnaire was sent to a corresponding author, and only 57% (seventeen) of the thirty authors replied. Only 13% (four) of thirty included studies used a receiver operator characteristic curve to calculate the accuracy of assessed inflammation markers. The rest of the studies used preestablished cutoffs for the assessed inflammation markers. The test definition, description, and value were inadequately described in most of the studies. The various cutoffs that were used are outlined in a table in the Appendix. The reported cutoffs used for white blood-cell count, erythrocyte sedimentation rate, and C-reactive protein level varied between 6000 and 12000 × 109/L, 12 and 40 mm/hr, and 0.3 and 13.5 mg/dL, respectively. Twelve (40%) of the thirty papers followed our best definition of prosthetic joint infection, twelve (40%) followed the good definition, and six (20%) followed the mediocre definition.

    Summary Estimates

    The summary receiver operator characteristic curves for white blood-cell count, erythrocyte sedimentation rate, C-reactive protein level, and interleukin-6 level for the thirty included studies were derived, and the area under the curve was calculated. The interleukin-6 and C-reactive protein level markers had a significantly higher diagnostic odds ratio than did the white blood-cell count and the erythrocyte sedimentation rate for discriminating infectious from noninfectious causes of revision arthroplasty. The pooled sensitivity was 45% (95% confidence interval, 41% to 49%) for the white blood-cell count, 75% (95% confidence interval, 72% to 77%) for the erythrocyte sedimentation rate, 88% (95% confidence interval, 86% to 90%) for the C-reactive protein level, and 97% (95% confidence interval, 93% to 99%) for the interleukin-6 level (p < 0.001). Pooled specificity for the same markers was 87% (95% confidence interval, 85% to 89%), 70% (95% confidence interval, 68% to 72%), 74% (95% confidence interval, 71% to 76%), and 91% (95% confidence interval, 87% to 94%), respectively (p < 0.001). This was confirmed by calculation of the Q value, which was higher for interleukin-6 levels (Q = 0.93; standard error, 0.12) and for C-reactive protein levels (Q = 0.81; standard error, 0.03) than for erythrocyte sedimentation rate (Q = 0.75; standard error, 0.02) or white blood-cell count (Q = 0.64; standard error, 0.03) (Figs. 2 through 5). The diagnostic odds ratio was significantly better for interleukin-6, followed by C-reactive protein level, erythrocyte sedimentation rate, and white blood-cell count (see Appendix).
     
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    Summary receiver operator characteristic curve (with 95% confidence interval) of all included studies that assessed C-reactive protein level as a diagnostic marker for prosthetic joint infection.

    Figure Description
     
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    Summary receiver operator characteristic curve (with 95% confidence interval) of all included studies that assessed white blood-cell count as a diagnostic marker for prosthetic joint infection.

    Figure Description
     
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    Summary receiver operator characteristic curve (with 95% confidence interval) of all included studies that assessed erythrocyte sedimentation rate as a diagnostic marker for prosthetic joint infection.

    Figure Description
     
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    Summary receiver operator characteristic curve of all included studies that assessed interleukin-6 level as a diagnostic marker for prosthetic joint infection.

    Figure Description

    Subgroup Analysis

    We performed a subgroup analysis on variables that were decided a priori: the site of the prosthesis (total hip arthroplasty versus total knee arthroplasty), whether or not a receiver operator characteristic curve was used, whether the study cohort was thought to be representative of the patients who will receive these tests in clinical practice, and the definition of prosthetic joint infection that was used (see Appendix). The diagnostic odds ratio was higher for total knee arthroplasty than for total hip arthroplasty for all three markers. The use of a receiver operator characteristic curve to determine the cutoffs and to analyze the markers in a representative population was associated with a higher diagnostic odds ratio. The cumulative mean number of studies (and standard deviation) with a "yes" answer to the twelve questions regarding QUADAS criteria for white blood-cell count, erythrocyte sedimentation rate, C-reactive protein level, and interleukin-6 were 8.6 ± 3.1, 8.5 ± 2.9, 9.25 ± 2.7, and 10.6 ± 1.5, respectively.
    Accurate preoperative identification of prosthetic joint infection in patients presenting with joint pain or radiographic periprosthetic lucencies is often difficult. Clinicians often rely on expensive nuclear imaging or more invasive studies such as joint aspiration for a more accurate diagnosis. Despite the best efforts, some patients with prosthetic joint infection will remain undiagnosed until the time of surgery. Therefore, having a marker with high sensitivity and specificity that is inexpensive and is done preoperatively is extremely useful for preoperative planning in cases of suspected infection. Based on this meta-analysis, we observed that serum interleukin-6 was associated with a high accuracy as a marker for periprosthetic infection, followed by the C-reactive protein level, the erythrocyte sedimentation rate, and the white blood-cell count.
    Kinetic properties of these markers are important when assessing their use in clinical practice as a diagnostic marker for prosthetic joint infection. Recently published studies have suggested that interleukin-6 may be a more accurate marker for infection than the C-reactive protein level or the erythrocyte sedimentation rate3. Interleukin-6 is produced by stimulated monocytes and macrophages, and it induces the production of several acute-phase proteins, including C-reactive protein. The serum interleukin-6 level in normal individuals is approximately 1 pg/mL, and it can increase to 30 to 430 pg/mL for as long as three days following total joint arthroplasty3,4. Interleukin-6 peaks at two days after uncomplicated arthroplasty and rapidly returns to a normal value. C-reactive protein is an acute-phase reactant that is produced by the liver in response to inflammation, infection, and neoplasm. Its levels are elevated to their peak values two to three days after surgery and return to normal approximately three weeks after surgery. Currently, most experts advocate the use of the blood erythrocyte sedimentation rate and C-reactive protein level as markers for assessing patients with a suspected prosthetic joint infection37-39. When both are negative, the likelihood of infection is extremely low. Following uncomplicated joint arthroplasty, the erythrocyte sedimentation rate increases, reaching a peak at five to seven days postoperatively, and then slowly decreases to preoperative levels in three to twelve months.
    The strength of the present review stems from reviewing the literature and collecting data by at least two independent reviewers, contacting authors of individual papers to confirm or correct the published data, accruing patient-level data from several studies, and using a random effects model, which represents a conservative approach that reflects the heterogeneity of the results.
    The present study also had several limitations. As the diagnostic threshold of each of the markers used is different among studies, we used the summary receiver operator characteristic curve method rather than a single point analysis. A large spectrum of patients suspected of having a prosthetic joint infection are represented in these studies, allowing generalization of our results to a variety of settings in clinical practice, but the study population and patient-selection methods were not fully reported in all studies. Due to the retrospective nature of most of these studies, there was a fair amount of withdrawal and enrichment with prosthetic joint infection cases. These markers were not routinely obtained for all patients undergoing surgery, resulting in a potential selection bias and exaggeration of accuracy. None of the studies provided information on blinding and test reproducibility. Our results are susceptible to spectrum bias, because diagnostic tests may have different accuracy in patients with early or late infections. Importantly, a strict case definition for prosthetic joint infection was not used in all studies. This could have led to a classification bias between infected and noninfected patients as sometimes the distinction between infection and contamination is difficult with certain organisms such as coagulase-negative staphylococci. However, we were unable to find a significant impact on the accuracy of the markers on the basis of the appropriateness of the case definition. Other factors that could have affected the accuracy but that were not reported in most of the studies included the use of antibiotics and the time between the assessment of serum markers and the validation of an infection. The means of measuring the white blood-cell count, erythrocyte sedimentation rate, C-reactive protein level, and interleukin-6 level were mostly not reported. Furthermore, there was some variation among the cutoff values of the tests that were used in different studies. While the accuracy of interleukin-6 for the diagnosis of prosthetic joint infection seems very promising, the current data are only driven by one large and two smaller studies. Only a few studies assessed the accuracy of combining different inflammation markers for the diagnosis of infection12,21,39. Finally, some degree of publication bias is unavoidable in systematic reviews. The small number of events and the wide confidence intervals also imply a level of uncertainty about inferences from these data.
    On the basis of this meta-analysis, we can conclude that the serum interleukin-6 level has the highest accuracy for the diagnosis of prosthetic joint infection, followed by the C-reactive protein level, the erythrocyte sedimentation rate, and the white blood-cell count. Further studies evaluating the accuracy of interleukin-6 and other cytokines in different patient populations are needed to confirm the findings of the present study.
    Supporting data tables are available with the electronic version of this article on our web site at jbjs.org (go to the article citation and click on "Supporting Data").
    Note: The authors of the present study acknowledge all of the authors of the included studies who took the time to reply to our queries and participated with their patient point data. They also thank Bettina Knoll, MD, and Davud Malekzadeh, Cand. med, for their help with translation of the German foreign language papers.
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    Sanzén  L;  Carlsson  AS. The diagnostic value of c-reactive protein in infected total hip arthroplasties. J Bone Joint Surg Br.  1989;71:638-41.[PubMed]
     
    Magnuson  JE;  Brown  ML;  Hauser  MF;  Berquist  TH;  Fitzgerald  RH  Jr;  Klee  GG. In-111-labeled leukocyte scintigraphy in suspected orthopedic prosthesis infection: comparison with other imaging modalities. Radiology.  1988;168:235-9.[PubMed]
     
    Kordelle  J;  Klett  R;  Stahl  U;  Hossain  H;  Schleicher  I;  Haas  H. [Infection diagnosis after knee -TEP- implantation.]Z Orthop Ihre Grenzgeb.  2004;142:337-43.  German.[PubMed][CrossRef]
     
    Klett  R;  Khalisi  A;  Haas  H;  Puille  M;  Steiner  D;  Stürz  H;  Bauer  R. [Staged diagnosis of septic hip endoprosthesis loosening with laboratory parameters and antigranulocyte scintigraphy]. Z Orthop Ihre Grenzgeb.  2001;139:415-9.  German.[PubMed][CrossRef]
     
    Parvizi  J;  Ghanem  E;  Menashe  S;  Barrack  RL;  Bauer  TW. Periprosthetic infection: what are the diagnostic challenges?J Bone Joint Surg Am.  2006;88  Suppl 4:138-47.[PubMed][CrossRef]
     
    Patel  R;  Osmon  DR;  Hanssen  AD. The diagnosis of prosthetic joint infection: current techniques and emerging technologies. Clin Orthop Relat Res.  2005;437:55-8.[PubMed][CrossRef]
     
    Spangehl  MJ;  Masterson  E;  Masri  BA;  O'Connell  JX;  Duncan  CP. The role of intraoperative gram stain in the diagnosis of infection during revision total hip arthroplasty. J Arthroplasty.  1999;14:952-6.[PubMed] [CrossRef]
     

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    Anchor for JumpAnchor for JumpFig. 1

    Flow chart illustrating the identification of articles that were eligible for inclusion in the systematic review. WBC = white blood-cell count, ESR = erythrocyte sedimentation rate, CRP = C-reactive protein level, IL-6 = interleukin-6.

    Figure Description
    Anchor for JumpAnchor for JumpFig. 2

    Summary receiver operator characteristic curve (with 95% confidence interval) of all included studies that assessed C-reactive protein level as a diagnostic marker for prosthetic joint infection.

    Figure Description
    Anchor for JumpAnchor for JumpFig. 3

    Summary receiver operator characteristic curve (with 95% confidence interval) of all included studies that assessed white blood-cell count as a diagnostic marker for prosthetic joint infection.

    Figure Description
    Anchor for JumpAnchor for JumpFig. 4

    Summary receiver operator characteristic curve (with 95% confidence interval) of all included studies that assessed erythrocyte sedimentation rate as a diagnostic marker for prosthetic joint infection.

    Figure Description
    Anchor for JumpAnchor for JumpFig. 5

    Summary receiver operator characteristic curve of all included studies that assessed interleukin-6 level as a diagnostic marker for prosthetic joint infection.

    Figure Description

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