Nuclear imaging does not have clear added value in patients with low a priori chance of periprosthetic joint infection. A retrospective single-center experience

Abstract. Background: A low-grade periprosthetic joint infection (PJI) may present without specific symptoms, and its diagnosis remains a challenge. Three-phase bone scintigraphy (TPBS) and white blood cell (WBC) scintigraphy are incorporated into recently introduced diagnostic criteria for PJI, but their exact value in diagnosing low-grade PJI in patients with nonspecific symptoms remains unclear. Methods: In this retrospective study, we evaluated patients with a prosthetic joint of the hip or knee who underwent TPBS and/or WBC scintigraphy between 2009 and 2016 because of nonspecific symptoms. We reviewed and calculated diagnostic accuracy of the TPBS and/or WBC scintigraphy to diagnose or exclude PJI. PJI was defined based on multiple cultures obtained during revision surgery. In patients who did not undergo revision surgery, PJI was ruled out by clinical follow-up of at least 2 years absent of clinical signs of infection based on MSIS 2011 criteria. Results: A total of 373 patients were evaluated, including 340 TPBSs and 142 WBC scintigraphies. Thirteen patients (3.5 %) were diagnosed with a PJI. TPBS sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were 71 %, 65 %, 8 % and 98 %, respectively. Thirty-five percent of TPBS showed increased uptake. Stratification for time intervals between the index arthroplasty and the onset of symptoms did not alter its diagnostic accuracy. WBC scintigraphy sensitivity, specificity, PPV and NPV were 30 %, 90 %, 25 % and 94 %, respectively. Conclusion: Nuclear imaging does not have clear added value in patients with low a priori chance of periprosthetic joint infection.

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The role of D-dimer in periprosthetic joint infection: a systematic review and meta-analysis

Diagnosis ◽

10.1515/dx-2021-0032 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Giovanni Balato ◽

Cristiano De Franco ◽

Fiamma Balboni ◽

Vincenzo De Matteo ◽

Tiziana Ascione ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Blood Sample ◽

Periprosthetic Joint Infection ◽

Meta Analysis ◽

Joint Infection ◽

Negative Likelihood Ratio ◽

Diagnostic Odds Ratio ◽

Receiver Operating Curve ◽

Sensitivity Specificity ◽

D Dimer

Abstract Objectives The current literature on diagnosis of periprosthetic joint infection (PJI) provides controversial evidence on the diagnostic accuracy of D-dimer. Therefore, this critical literature search and meta-analysis was aimed to summarize the diagnostic accuracy of D-dimer for diagnosing PJI. Content We searched MEDLINE, Scopus, and Web of Science, for studies on D-dimer for diagnosing PJI, according to the PRISMA flowchart. QUADAS was used for assessing study quality. Sensitivity, specificity, positive (PLR) and negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were analyzed using bivariate diagnostic random-effects model. The area under the receiver-operating curve (AUC-ROC) was calculated. Subgroup analysis and univariate meta-regression were carried out for detecting potential sources of heterogeneity. Summary We included 12 articles, totaling 1,818 patients (539 with PJI). The pooled sensitivity and specificity of D-dimer for diagnosing PJI were 0.739 (95% CI: 0.616–0.833) and 0.785 (95% CI: 0.679–0.863). The pooled PLR, NLR, DOR were 3.359 (95% CI, 2.340–4.821), 0.295 (95% CI, 0.180–0.484), and 11.787 (95% CI, 5.785–24.018). The cumulative ROC plot displayed an AUC of 0.688 (95% CI, 0.663–0.713; p<0.001). No threshold effects could be observed. The type of blood sample was identified as possible source of heterogeneity for DOR (p=0.01). Outlook Evidence emerged from this meta-analysis suggests that D-dimer displays sufficient diagnostic accuracy to rule out PJI. The type of blood sample (plasma vs. serum) and the study design could influence the results in terms of DOR and sensitivity. However, further perspective studies would be needed to validate its potential diagnostic usefulness.

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The significance of synovial biopsy in the diagnostic workup of the low-grade periprosthetic joint infection of shoulder arthroplasty

Archives of Orthopaedic and Trauma Surgery ◽

10.1007/s00402-021-03932-x ◽

2021 ◽

Author(s):

Moritz Mederake ◽

Ulf Krister Hofmann ◽

Bernd Fink

Keyword(s):

Revision Surgery ◽

Periprosthetic Joint Infection ◽

Shoulder Arthroplasty ◽

Joint Infection ◽

Diagnostic Value ◽

Synovial Biopsy ◽

Diagnostic Workup ◽

Low Grade ◽

Diagnostic Challenge ◽

Shoulder Arthroplasties

Abstract Introduction A common reason for painful shoulder arthroplasties and revision surgery is a low-grade periprosthetic joint infection (PJI). Diagnosing a low-grade infection is, however, a major diagnostic challenge. This applies even more to the shoulder, which differs from other large joints in terms of clinical features and microbiological spectrum. Aim of this study was to evaluate the diagnostic value of the synovial biopsy in the diagnostic workup of low-grade PJI of the shoulder. Materials and methods A retrospective evaluation was conducted on 56 patients receiving revision surgery on their shoulder arthroplasty. A standardized preoperative workup was performed comprising CRP value, leukocyte blood count, synovial fluid microbiological analyses and leukocyte count from joint aspiration, and five synovial biopsy samples for bacteriologic and histologic analysis obtained through an arthroscopic approach. During revision surgery, five samples of periprosthetic tissue were harvested for bacteriologic and histologic analyses. The MSIS-Criteria 2014 were used to evaluate the diagnostic results. Results In total, 15 of 56 revised prostheses turned out as PJI (27%). When applying our diagnostic workup, we obtained a sensitivity of 67% with a specificity of 95%. When performing a subgroup analysis on those patients that had received diagnostic biopsy, a sensitivity of 100% and a specificity of 83% could be achieved. With a sensitivity and specificity of 90% and 83%, respectively, the biopsy is the single method with the highest diagnostic value. Conclusions The sensitivity of only 67% of our standard workup emphasizes the difficulty to adequately diagnose low-grade infections after shoulder arthroplasty. The excellent specificity of 95% ensures, however, that non-infected prostheses are not incorrectly explanted. This study highlights that synovial biopsy has a high diagnostic value and should be done prior to complex revision surgeries to raise sensitivity in diagnosing a PJI.

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Synovial Complement Factors in Patients with Periprosthetic Joint Infection after Undergoing Revision Arthroplasty of the Hip or Knee Joint

Diagnostics ◽

10.3390/diagnostics11030434 ◽

2021 ◽

Vol 11 (3) ◽

pp. 434

Author(s):

Frank Sebastian Fröschen ◽

Sophia Schell ◽

Matthias Dominik Wimmer ◽

Gunnar Thorben Rembert Hischebeth ◽

Hendrik Kohlhof ◽

...

Keyword(s):

Synovial Fluid ◽

Multiple Regression ◽

Complement System ◽

Periprosthetic Joint Infection ◽

Joint Infection ◽

Expression Patterns ◽

Factor H ◽

Low Grade ◽

Complement Factors ◽

Fluid Levels

The role and diagnostic value of the synovial complement system in patients with low-grade periprosthetic joint infection (PJI) are unclear. We sought to evaluate, for the first time, the usefulness of synovial complement factors in these patients by measuring the individual synovial fluid levels of complement factors (C1q, C3b/iC3b, C4b, C5, C5a, C9, factor B, factor D, factor H, factor I, properdin, and mannose-binding lectin [MBL]). The patients (n = 74) were classified into septic (n = 28) and aseptic (n = 46). Receiver-operator characteristic curves and a multiple regression model to determine the feasibility of a combination of the tested cytokines to determine the infection status were calculated. The synovial fluid levels of C1q, C3b/C3i, C4b, C5, C5a, MBL, and properdin were significantly elevated in the PJI group. The best sensitivity and specificity was found for C1q. The multiple regression models revealed that the combination of C1q, C3b/C3i, C4b, C5, C5a, and MBL was associated with the best sensitivity (83.3%) and specificity (79.2%) for a cutoff value of 0.62 (likelihood ratio: 4.0; area under the curve: 0.853). Nevertheless, only a combined model showed acceptable results. The expression patterns of the complement factors suggested that PJI activates all three pathways of the complement system.

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A Study of the Diagnostic Accuracy of an Existing Multivariable Test to Predict Shoulder Dystocia

American Journal of Perinatology Reports ◽

10.1055/s-0039-1693162 ◽

2019 ◽

Vol 09 (03) ◽

pp. e262-e267

Author(s):

Henry Alexander Easley ◽

Todd Michael Beste

Keyword(s):

Diagnostic Accuracy ◽

Prediction Model ◽

Study Design ◽

False Positive ◽

False Positive Rate ◽

Shoulder Dystocia ◽

The Other ◽

Predictive Values ◽

Positive Rate ◽

Sensitivity Specificity

Objectives To evaluate the diagnostic accuracy of a multivariable prediction model, the Shoulder Screen (Perigen, Inc.), and compare it with the American College of Obstetricians and Gynecologists (ACOG) guidelines to prevent harm from shoulder dystocia. Study Design The model was applied to two groups of 199 patients each who delivered during a 4-year period. One group experienced shoulder dystocia and the other group delivered without shoulder dystocia. The model's accuracy was analyzed. The performance of the model was compared with the ACOG guideline. Results The sensitivity, specificity, positive, and negative predictive values of the model were 23.1, 99.5, 97.9, and 56.4%, respectively. The sensitivity of the ACOG guideline was 10.1%. The false-positive rate of the model was 0.5%. The accuracy of the model was 61.3%. Conclusion A multivariable prediction model can predict shoulder dystocia and is more accurate than ACOG guidelines.

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Diagnostic accuracy of alpha-defensin enzyme-linked immunosorbent assay in the clinical evaluation of painful hip and knee arthroplasty with possible prosthetic joint infection

The Bone & Joint Journal ◽

10.1302/0301-620x.101b8.bjj-2018-1390.r2 ◽

2019 ◽

Vol 101-B (8) ◽

pp. 970-977 ◽

Cited By ~ 11

Author(s):

S. Kleiss ◽

N. M. Jandl ◽

A. Novo de Oliveira ◽

W. Rüther ◽

A. Niemeier

Keyword(s):

Synovial Fluid ◽

Diagnostic Accuracy ◽

Immunosorbent Assay ◽

Knee Arthroplasty ◽

Prosthetic Joint Infection ◽

Joint Infection ◽

Enzyme Linked Immunosorbent Assay ◽

Coagulase Negative Staphylococci ◽

Predictive Values ◽

Prosthetic Joint

Aims The aim of this study was to evaluate the diagnostic accuracy of the synovial alpha-defensin enzyme-linked immunosorbent assay (ELISA) for the diagnosis of prosthetic joint infection (PJI) in the work-up prior to revision of total hip (THA) and knee arthroplasty (TKA). Patients and Methods Inclusion criteria for this prospective cohort study were acute or chronic symptoms of the index joint without specific exclusion criteria. Synovial fluid aspirates of 202 patients were analyzed and semiquantitative laboratory alpha-defensin ELISA was performed. Final diagnosis of PJI was established by examination of samples obtained during revision surgery. Results Sensitivity and specificity of the alpha-defensin ELISA for PJI were 78.2% (95% confidence interval (CI) 66.7 to 88.5) and 96.6% (95% CI 93.0 to 99.3). Positive and negative predictive values were 89.6% (95% CI 80.6 to 97.8) and 92.2% (95% CI 87.5 to 96.1). The test remained false-negative in 22% of septic revisions, most of which were due to coagulase-negative staphylococci all occurring in either late-chronic or early-postoperative PJI. Conclusion The routine use of synovial fluid alpha-defensin laboratory ELISA in the preoperative evaluation of symptomatic THAs and TKAs is insufficient to accurately diagnose PJI. Particularly in cases involving low-virulence organisms, such as coagulase-negative staphylococci, there remains a need for tests with a higher sensitivity. Cite this article: Bone Joint J 2019;101-B:970–977.

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Diagnostic Accuracy of Machine Learning-Based Radiomics in Grading Gliomas: Systematic Review and Meta-Analysis

Contrast Media & Molecular Imaging ◽

10.1155/2020/2127062 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Curtis K. Sohn ◽

Sotirios Bisdas

Keyword(s):

Machine Learning ◽

Diagnostic Accuracy ◽

Diagnostic Performance ◽

Meta Analysis ◽

Total Sample ◽

Low Grade ◽

Sample Sizes ◽

Summary Receiver Operating Characteristic ◽

Pubmed Database ◽

Sensitivity Specificity

Purpose. This study aimed to estimate the diagnostic accuracy of machine learning- (ML-) based radiomics in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG) and to identify potential covariates that could affect the diagnostic accuracy of ML-based radiomic analysis in classifying gliomas. Method. A primary literature search of the PubMed database was conducted to find all related literatures in English between January 1, 2009, and May 1, 2020, with combining synonyms for “machine learning,” “glioma,” and “radiomics.” Five retrospective designed original articles including LGG and HGG subjects were chosen. Pooled sensitivity, specificity, their 95% confidence interval, area under curve (AUC), and hierarchical summary receiver-operating characteristic (HSROC) models were obtained. Result. The pooled sensitivity when diagnosing HGG was higher (96% (95% CI: 0.93, 0.98)) than the specificity when diagnosing LGG (90% (95% CI 0.85, 0.93)). Heterogeneity was observed in both sensitivity and specificity. Metaregression confirmed the heterogeneity in sample sizes ( p = 0.05 ), imaging sequence types ( p = 0.02 ), and data sources ( p = 0.01 ), but not for the inclusion of the testing set ( p = 0.19 ), feature extraction number ( p = 0.36 ), and selection of feature number ( p = 0.18 ). The results of subgroup analysis indicate that sample sizes of more than 100 and feature selection numbers less than the total sample size positively affected the diagnostic performance in differentiating HGG from LGG. Conclusion. This study demonstrates the excellent diagnostic performance of ML-based radiomics in differentiating HGG from LGG.

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Feasibility and Validity of Computed Tomography-Derived Fractional Flow Reserve in Patients With Severe Aortic Stenosis

Circulation Cardiovascular Interventions ◽

10.1161/circinterventions.120.009586 ◽

2020 ◽

Author(s):

Michael Michail ◽

Abdul-Rahman Ihdayhid ◽

Andrea Comella ◽

Udit Thakur ◽

James D. Cameron ◽

...

Keyword(s):

Aortic Stenosis ◽

Diagnostic Accuracy ◽

Operating Characteristic ◽

Severe Aortic Stenosis ◽

Characteristic Curve ◽

Fractional Flow ◽

Predictive Values ◽

Flow Reserve ◽

Artery Disease ◽

Sensitivity Specificity

Background: Coronary artery disease is common in patients with severe aortic stenosis. Computed tomography-derived fractional flow reserve (CT-FFR) is a clinically used modality for assessing coronary artery disease, however, its use has not been validated in patients with severe aortic stenosis. This study assesses the safety, feasibility, and validity of CT-FFR in patients with severe aortic stenosis. Methods: Prospectively recruited patients underwent standard-protocol invasive FFR and coronary CT angiography (CTA). CTA images were analyzed by central core laboratory (HeartFlow, Inc) for independent evaluation of CT-FFR. CT-FFR data were compared with FFR (ischemia defined as FFR ≤0.80). Results: Forty-two patients (68 vessels) underwent FFR and CTA; 39 patients (92.3%) and 60 vessels (88.2%) had interpretable CTA enabling CT-FFR computation. Mean age was 76.2±6.7 years (71.8% male). No patients incurred complications relating to premedication, CTA, or FFR protocol. Mean FFR and CT-FFR were 0.83±0.10 and 0.77±0.14, respectively. CT calcium score was 1373.3±1392.9 Agatston units. On per vessel analysis, there was positive correlation between FFR and CT-FFR (Pearson correlation coefficient, R =0.64, P <0.0001). Sensitivity, specificity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and 82.9%, respectively, with 76.7% diagnostic accuracy. The area under the receiver-operating characteristic curve for CT-FFR was 0.83 (0.72–0.93, P <0.0001), which was higher than that of CTA and quantitative coronary angiography ( P =0.01 and P <0.001, respectively). Bland-Altman plot showed mean bias between FFR and CT-FFR as 0.059±0.110. On per patient analysis, the sensitivity, specificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and 81.0% with 76.9% diagnostic accuracy. The per patient area under the receiver-operating characteristic curve analysis was 0.81 (0.67–0.95, P <0.0001). Conclusions: CT-FFR is safe and feasible in patients with severe aortic stenosis. Our data suggests that the diagnostic accuracy of CT-FFR in this cohort potentially enables its use in clinical practice and provides the foundation for future research into the use of CT-FFR for coronary evaluation pre-aortic valve replacement.

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The diagnostic effect of α-defensin, D-dimer, and IL-6 in periprosthetic joint infection: A systematic review and diagnostic meta-analysis

Journal of Orthopaedic Surgery ◽

10.1177/2309499020971861 ◽

2020 ◽

Vol 28 (3) ◽

pp. 230949902097186

Author(s):

Baozhong Tian ◽

Liwen Cui ◽

Weihai Jiang

Keyword(s):

Systematic Review ◽

Sensitivity And Specificity ◽

Periprosthetic Joint Infection ◽

Meta Analysis ◽

Joint Infection ◽

Common Complication ◽

Online Databases ◽

Artificial Joint Replacement ◽

Sensitivity Specificity ◽

D Dimer

Background: Periprosthetic joint infection (PJI) is the most common complication after artificial joint replacement as previously reported. However, the main problem at present is its difficulty in diagnosis. This systematic review and meta-analysis aimed to compare the diagnostic accuracy of α-defensin, D-dimer, and interleukin-6 (IL-6) in clinical practice. Method: Online databases were systematically searched until June 18th, 2020 with keywords and medical sub-headings terms. Studies mentioned the sensitivity and specificity of biological markers in detecting PJI were included in our study. The sensitivity, specificity, and diagnostic odds ratios (DORs) were obtained after integration. Results: A total of 34 studies with 1036 patients diagnosing as PJI were included for comparing α-defensin, D-dimer, and IL-6. The sensitivity and specificity of α-defensin for PJI were 0.88 and 0.96, and the DOR was 189 (95% CI 72–496), respectively. The sensitivity and specificity of D-dimer (0.82 and 0.72) and IL-6 (0.80 and 0.89) were lower than α-defensin. Conclusion: The detection of α-defensin is a promising biomarker for diagnosing PJI. The optional cut-off needs to be curtained when using other biomarkers.

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Salmonella Sp. as the Cause of Periprosthetic Joint Infection of the Hip: Report of a Rare Case and Literature Review

Orthopaedic Journal of Sports Medicine ◽

10.1177/2325967120s00049 ◽

2020 ◽

Vol 8 (5_suppl5) ◽

pp. 2325967120S0004

Author(s):

Asep Santoso ◽

Iwan Budiwan Anwar ◽

Tangkas Sibarani ◽

Bintang Soetjahjo ◽

Ismail Mariyanto

Keyword(s):

Total Hip Arthroplasty ◽

Literature Review ◽

Antibiotic Treatment ◽

Hip Arthroplasty ◽

Revision Surgery ◽

Periprosthetic Joint Infection ◽

Rare Case ◽

Joint Infection ◽

Immunosuppressed Patient ◽

Cement Spacer

Periprosthetic joint infection of the hip due to Salmonella sp. is rare. It is sometimes difficult to treat and needed a prolonged antibiotic treatment. We reported a case of periprosthetic joint infection of the hip in a 67 years old female who received prior left total hip arthroplasty. Two-stage revision surgery with antibiotic-loaded cement spacer has been performed to the patient and successfully control the infection. Review of the literatures also has been done. Salmonella Sp. has to be considered as one of differential etiology in the case of infected arthroplasty especially in an immunosuppressed patient. It showed still there has been no consensus in the treatment of choice for this particular case.

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