Literature DB >> 29305426

Rapid detection of periprosthetic joint infection using a combination of 16s rDNA polymerase chain reaction and lateral flow immunoassay: A Pilot Study.

V Janz1, J Schoon2, C Morgenstern3, B Preininger3, S Reinke2, G Duda2, A Breitbach4, C F Perka5, S Geissler2.   

Abstract

OBJECTIVES: The objective of this study was to develop a test for the rapid (within 25 minutes) intraoperative detection of bacteria from synovial fluid to diagnose periprosthetic joint infection (PJI).
METHODS: The 16s rDNA test combines a polymerase chain reaction (PCR) for amplification of 16s rDNA with a lateral flow immunoassay in one fully automated system. The synovial fluid of 77 patients undergoing joint aspiration or primary or revision total hip or knee surgery was prospectively collected. The cohort was divided into a proof-of-principle cohort (n = 17) and a validation cohort (n = 60). Using the proof-of-principle cohort, an optimal cut-off for the discrimination between PJI and non-PJI samples was determined. PJI was defined as detection of the same bacterial species in a minimum of two microbiological samples, positive histology, and presence of a sinus tract or intra-articular pus.
RESULTS: The 16s rDNA test proved to be very robust and was able to provide a result in 97% of all samples within 25 minutes. The 16s rDNA test was able to diagnose PJI with a sensitivity of 87.5% and 82%, and a specificity of 100% and 89%, in the proof-of-principle and validation cohorts, respectively. The microbiological culture of synovial fluid achieved a sensitivity of 80% and a specificity of 93% in the validation cohort.
CONCLUSION: The 16s rDNA test offers reliable intraoperative detection of all bacterial species within 25 minutes with a sensitivity and specificity comparable with those of conventional microbiological culture of synovial fluid for the detection of PJI. The 16s rDNA test performance is independent of possible blood contamination, culture time and bacterial species.Cite this article: V. Janz, J. Schoon, C. Morgenstern, B. Preininger, S. Reinke, G. Duda, A. Breitbach, C. F. Perka, S. Geissler. Rapid detection of periprosthetic joint infection using a combination of 16s rDNA polymerase chain reaction and lateral flow immunoassay: A Pilot Study. Bone Joint Res 2018;7:12-19. DOI: 10.1302/2046-3758.71.BJR-2017-0103.R2.
© 2018 Janz et al.

Entities:  

Keywords:  16s rDNA; Immunoassay; Lateral flow; Periprosthetic joint infection; Polymerase chain reaction; Rapid detection

Year:  2018        PMID: 29305426      PMCID: PMC5805835          DOI: 10.1302/2046-3758.71.BJR-2017-0103.R2

Source DB:  PubMed          Journal:  Bone Joint Res        ISSN: 2046-3758            Impact factor:   5.853


This study presents the initial results of a newly developed test for the rapid (within 25 minutes) intraoperative detection of bacteria from synovial fluid to detect periprosthetic joint infection (PJI). The 16s rDNA test combines a polymerase chain reaction (PCR) for amplification of 16s rDNA with a lateral flow immunoassay in one fully automated system. The 16s rDNA test was able to provide a result in 97% of all samples within 25 minutes. The sensitivity and specificity of the 16s rDNA test were comparable with the sensitivity and specificity of conventional synovial fluid culture. This study is the first to develop a 16s rDNA based test within 25 minutes, allowing for a true intraoperative application. Initial results of a pilot study. Future prospective studies for intraoperative application and specialized surgical indications are planned.

Introduction

Before a revision of a total hip arthroplasty (THA) or total knee arthroplasty (TKA), it is mandatory to either confirm or exclude a periprosthetic joint infection (PJI), since the surgical strategies differ significantly between aseptic and septic revisions. In cases of an unclear preoperative diagnosis of PJI, the only other routinely utilized diagnostic option is the histological evaluation of an intraoperative frozen tissue section.[1] A previous meta-analysis by Tsaras et al[2] has reported convincing diagnostic evidence for the use of frozen tissue sections for the detection of culture-positive PJI in TKA and THA, with a diagnostic odds ratio of 54.7. However, currently there are no commonly utilized diagnostic alternatives for cases of unclear PJI status. Although a post hoc differentiation between septic and aseptic cases is possible through other non-culture-based diagnostic methods, such as synovial cell count, leucocyte esterase, and α-defensin, none of these have been validated as a diagnostic tool to facilitate intraoperative decision-making.[3-8] Additionally, all of these diagnostic methods are dependent on the patient’s immune response towards the presence of bacteria and therefore only allow for an indirect detection of PJI. It was the goal of this study to design a diagnostic test for an intraoperative discrimination between septic and aseptic cases through a direct detection of the causative bacterial species. To enable an intraoperative diagnosis, a bacterial infection has to be directly detected in order to circumvent the delay due to microbiological culture. A direct detection of bacteria can be realized by multiplex polymerase chain reaction (PCR)-based amplification of 16s rDNA, which encodes highly conservative regions of the 16s ribosomal subunit and is common to all bacterial species. The detection of 16s rDNA, through multiplex PCR, can be performed from different sample materials, such as synovial fluid, periprosthetic tissue samples, and sonicate fluid.[9-13] Synovial fluid is the most promising material for such purposes due to the ease of acquisition at the beginning of revision surgery and the wide acceptance within the surgical community of its use to diagnose PJI.[13-16] To our knowledge, there are currently only two other studies that were able to achieve a ‘rapid’ molecular diagnosis of PJI, within three hours and 4.5 hours, respectively.[12,17,18] While this represents a significant improvement over the standard diagnostic time of culture-based methods, this timeframe is still too great for a true intraoperative application to discriminate between septic and aseptic failures. The aim of this study was to develop a 16s rDNA PCR test system for the detection of PJI that would rapidly (within 25 minutes) facilitate intraoperative discrimination between septic and aseptic prosthetic joint failures.

Patients and Methods

Study design and patient cohort

A total of 77 patients were included in this prospective cohort study, between January 2014 and January 2015, and divided into a proof-of-principle cohort (n = 17, eight cases of PJI) and a validation cohort (n = 60, 23 cases of PJI). The sample size of the validation cohort was determined by power analysis based on the results from the proof-of-principle group (power = 0.80, a = 0.01; two-sided, minimum sample size = 21 per group). All patients provided written informed consent, and the study was approved by the local institutional review board. The proof-of-principle cohort was used to evaluate the test’s functionality and to assess the optimal threshold for discrimination between septic and aseptic patients. The validation cohort was used to evaluate the test’s diagnostic performance. Synovial fluid samples were collected preoperatively for the THA and TKA revisions with a preoperative suspicion of PJI, or intraoperatively for THA and TKA revisions without preoperative suspicion of PJI. In addition, synovial aspirations of native joints were performed intra-operatively during primary THA and TKA surgery. These aspirations of native joints functioned exclusively as aseptic negative controls. Within one hour, the samples were transported to our research facility and frozen at -80°C prior to analysis. The proof-of-principle cohort was comprised of two primary TKAs, ten revision THAs or TKAs, and five THA aspirations (Table I). The validation cohort was comprised of seven primary THAs or TKAs, 32 revision THAs or TKAs, and 21 joint aspirations (Table II). Sample harvesting, patient/sample data collection, and documentation were performed in accordance with our institutional guidelines.[19] The physical properties of the samples were qualitatively assessed, including variances in synovial viscosity, optical clarity (blood contamination), and sample volumes.
Table I.

Patient and sample characterization for the proof-of-concept cohort (PC)

Sample IDGenderAge (yrs)Preoperative suspicion[*]Surgical procedureMicrobiological culture[]PJI[]16s rDNA assay
PC_01Male19AsepticPrimary THA/TKAN/ANegativeNegative
PC_02Female84AsepticPrimary THA/TKAN/ANegativeNegative
PC_03Male55AsepticRevision THA/TKANegativeNegativeNegative
PC_04Female52AsepticRevision THA/TKANegativeNegativeNegative
PC_05Female60AsepticRevision THA/TKANegativeNegativeNegative
PC_06Female71SepticRevision THA/TKANegativeNegativeNegative
PC_07Female47SepticRevision THA/TKANegativeNegativeNegative
PC_08Male87UnclearJoint aspirationNegativeNegativeNegative
PC_09Male68UnclearJoint aspirationNegativeNegativeNegative
PC_10Male37SepticRevision THA/TKAPositivePositiveNegative
PC_11Female76SepticRevision THA/TKAPositivePositivePositive
PC_12Male60SepticRevision THA/TKANegativePositivePositive
PC_13Female90SepticRevision THA/TKAPositivePositivePositive
PC_14Male85UnclearJoint aspirationPositivePositivePositive
PC_15Male87UnclearJoint aspirationPositivePositivePositive
PC_16Male74UnclearJoint aspirationPositivePositivePositive
PC_17Male66UnclearRevision THA/TKAPositivePositivePositive

Based on the preoperative diagnostics

Growth of the same bacterial species in at least two of the following samples: synovial fluid, intraoperative tissue sample, and sonicate fluid cultures (SFC)

Final diagnosis of PJI based on intraoperative samples and PJI definition

PJI, periprosthetic joint infection; THA, total hip arthroplasty; TKA, total knee arthroplasty; N/A, not available

Table II.

Patient and sample characterization for the validation cohort (VC)

Sample IDGenderAge (yrs)Preoperative suspicion[*]Surgical procedureMicrobiological culture[]PJI[]16s rDNA assay
VC_01Female65AsepticPrimary THA/TKAN/ANegativeNegative
VC_02Male46AsepticPrimary THA/TKAN/ANegativeNegative
VC_03Female83AsepticPrimary THA/TKAN/ANegativeNegative
VC_04Male48AsepticPrimary THA/TKAN/ANegativeNegative
VC_05Male62AsepticPrimary THA/TKAN/ANegativeNegative
VC_06Male71AsepticPrimary THA/TKAN/ANegativeNegative
VC_07Male81AsepticPrimary THA/TKAN/ANegativeNegative
VC_08Male81AsepticRevision THA/TKANegativeNegativePositive
VC_09Male56AsepticRevision THA/TKANegativeNegativeNegative
VC_10Female78AsepticRevision THA/TKANegativeNegativeNegative
VC_11Female59AsepticRevision THA/TKANegativeNegativeNegative
VC_12Female79AsepticRevision THA/TKANegativeNegativeNegative
VC_13Male54AsepticRevision THA/TKANegativeNegativeNegative
VC_14Female51AsepticRevision THA/TKANegativeNegativeNegative
VC_15Male79SepticRevision THA/TKANegativeNegativeNegative
VC_16Female52SepticRevision THA/TKANegativeNegativePositive
VC_17Female46SepticRevision THA/TKANegativeNegativeNegative
VC_18Female70SepticRevision THA/TKANegativeNegativeNegative
VC_19Female59SepticRevision THA/TKANegativeNegativeNegative
VC_20Female70SepticRevision THA/TKANegativeNegativeNegative
VC_21Male37UnclearJoint aspirationNegativeNegativePositive
VC_22Male62UnclearJoint aspirationNegativeNegativeNegative
VC_23Male55UnclearJoint aspirationNegativeNegativeNegative
VC_24Male67UnclearJoint aspirationNegativeNegativeNegative
VC_25Male77UnclearJoint aspirationNegativeNegativeNegative
VC_26Female77UnclearJoint aspirationPositiveNegativeN/A
VC_27Male46UnclearJoint aspirationNegativeNegativeNegative
VC_28Male60UnclearJoint aspirationNegativeNegativePositive
VC_29Male72UnclearJoint aspirationNegativeNegativeNegative
VC_30Male73UnclearJoint aspirationNegativeNegativeNegative
VC_31Male68UnclearJoint aspirationNegativeNegativeNegative
VC_32Male86UnclearJoint aspirationNegativeNegativeNegative
VC_33Female77UnclearJoint aspirationNegativeNegativeNegative
VC_34Female71UnclearRevision THA/TKANegativeNegativeNegative
VC_35Female70UnclearRevision THA/TKANegativeNegativeNegative
VC_36Male85UnclearRevision THA/TKANegativeNegativeNegative
VC_37Male74UnclearRevision THA/TKANegativeNegativeNegative
VC_38Male61SepticJoint aspirationPositivePositiveNegative
VC_39Female89SepticRevision THA/TKAPositivePositivePositive
VC_40Female76SepticRevision THA/TKANegativePositivePositive
VC_41Female80SepticRevision THA/TKAPositivePositiveNegative
VC_42Female78SepticRevision THA/TKAPositivePositivePositive
VC_43Female70SepticRevision THA/TKAPositivePositivePositive
VC_44Male66SepticRevision THA/TKAPositivePositiveNegative
VC_45Male60SepticRevision THA/TKAPositivePositivePositive
VC_46Male66SepticRevision THA/TKAPositivePositivePositive
VC_47Male63SepticRevision THA/TKAPositivePositiveNegative
VC_48Female75SepticRevision THA/TKAPositivePositivePositive
VC_49Male59SepticRevision THA/TKANegativePositivePositive
VC_50Male70UnclearRevision THA/TKANegativePositiveN/A
VC_51Female55UnclearJoint aspirationPositivePositivePositive
VC_52Female55UnclearJoint aspirationPositivePositivePositive
VC_53Male66UnclearJoint aspirationPositivePositivePositive
VC_54Male84UnclearJoint aspirationPositivePositivePositive
VC_55Male86UnclearJoint aspirationPositivePositivePositive
VC_56Female64UnclearJoint aspirationPositivePositivePositive
VC_57Male73UnclearJoint aspirationPositivePositivePositive
VC_58Female67UnclearRevision THA/TKANegativePositivePositive
VC_59Female78UnclearRevision THA/TKAPositivePositivePositive
VC_60Male65UnclearRevision THA/TKAPositivePositivePositive

Based on the preoperative diagnostics

Growth of the same bacterial species in at least two of the following samples: synovial fluid, intraoperative tissue sample, and sonicate fluid cultures (SFC)

Final diagnosis of PJI based on intraoperative samples and PJI definition

PJI, periprosthetic joint infection; THA, total hip arthroplasty; TKA, total knee arthroplasty; N/A, not available

Patient and sample characterization for the proof-of-concept cohort (PC) Based on the preoperative diagnostics Growth of the same bacterial species in at least two of the following samples: synovial fluid, intraoperative tissue sample, and sonicate fluid cultures (SFC) Final diagnosis of PJI based on intraoperative samples and PJI definition PJI, periprosthetic joint infection; THA, total hip arthroplasty; TKA, total knee arthroplasty; N/A, not available Patient and sample characterization for the validation cohort (VC) Based on the preoperative diagnostics Growth of the same bacterial species in at least two of the following samples: synovial fluid, intraoperative tissue sample, and sonicate fluid cultures (SFC) Final diagnosis of PJI based on intraoperative samples and PJI definition PJI, periprosthetic joint infection; THA, total hip arthroplasty; TKA, total knee arthroplasty; N/A, not available

PJI definition and intraoperative sample acquisition

PJI was defined according to the following criteria: intra-articular pus or presence of a sinus tract; histology indicative of infection (type II or III periprosthetic membrane); or positive microbiological culture of the same bacterial species in a minimum of two of the following samples: synovial fluid; intraoperative tissue sample; or sonicate fluid cultures (SFC).[20-23] The final diagnosis of PJI was made according to the results of the intraoperative microbiological and histological samples. The final diagnosis of PJI was the benchmark reference, against which the performance of the 16s rDNA test, as well as all calculations for sensitivity and specificity, were referenced. Synovial fluid sampling was performed in an operating theatre with laminar air flow, utilizing a skin incision, and under fluoroscopic guidance, for all joint aspirations. Intraoperative synovial fluid aspiration was performed under direct visualization of the joint and prior to capsulotomy. Additionally, multiple periprosthetic tissue samples, a histological sampling of the periprosthetic membrane, and SFC were acquired for all cases of revision arthroplasty. The histological evaluation was performed according to the consensus classification of the periprosthetic interface membrane.[21] To optimize the microbiological culture methods, both synovial fluid and SFC were incubated in blood culture bottles.[24-26] Intraoperative tissue samples were cultured on standard agar plates. To allow for a detection of fastidious bacterial species, all microbiological cultures were incubated for 14 days.[27]

16s rDNA PCR test system

The 16s rDNA test is based on a targeted PCR and subsequent detection of the PCR products by lateral flow immunoassay. The 16s rDNA test was performed from intraoperatively acquired synovial fluid. The PCR primers target a highly conservative region of the 16s ribosomal subunit that is common to all bacterial species. The complete workflow is illustrated in Figure 1 and requires 25 minutes. Synovial fluid (total volume = 2 µl) was directly combined with the PCR master mix, containing differentially labelled forward (biotin) and reverse (Fluorescein isothiocyanate (FITC)) primers that are specific to a highly conserved 16s rDNA sequence (primers are available on request; Milenia Biotec GmbH, Gießen, Germany). Polymerase chain reaction (30 cycles; 15 minutes) was performed using the Labcycler 48s (SensoQuest GmbH, Göttingen, Germany). In the presence of 16s rDNA, the PCR produced double-labelled (biotin and FITC) DNA products. The PCR mixture was subsequently transferred to the lateral flow immunoassay test unit (Milenia Biotec), where the PCR fragments were captured via their biotin label by specific antibodies in a single-step procedure. The results were displayed as two bands on the test strip. The lower test band indicates the detection of the bacterial 16s rDNA product and the upper band serves as a control, confirming the correct function of the flow assay. The test results were evaluated by spectrometric measurement of the band intensity and quantified by ImageJ software (National Institutes of Health, Bethesda, Maryland; http://imagej.nih.gov).[28] The 16s rDNA assay score was calculated as the ratio between the intensity of the test and control bands and expressed in arbitrary units (AU).

General workflow of the 16s rDNA test: a) chronological test principle, with polymerase chain reaction (PCR) followed by subsequent detection of the specific PCR products by lateral flow immunoassay; b) the results are displayed as one test band (T, detection of 16s rDNA); and c) a control band (C), confirming the correct function of assay).

General workflow of the 16s rDNA test: a) chronological test principle, with polymerase chain reaction (PCR) followed by subsequent detection of the specific PCR products by lateral flow immunoassay; b) the results are displayed as one test band (T, detection of 16s rDNA); and c) a control band (C), confirming the correct function of assay).

Statistical analysis

All data are given as mean ± sd. The Mann–Whitney U test was used for group comparison and receiver operating characteristic (ROC) analysis was performed to determine the optimal cut-off for discrimination between the two patient groups. Assay sensitivity and specificity were calculated as previously described.[29] Sensitivity was defined as true positive (TP) / (TP + false negative (FN)), and specificity was defined as true negative (TN) / (TN + false positive (FP)), All statistical analyses were performed with SPSS software, version 18 (IBM Corp., Armonk, New York), and statistical significance was defined at p < 0.05. The medical patient data and the results from the 16s rDNA PCR test system were evaluated in a double-blinded manner by two authors (SG and VJ).

Results

Test reliability

The 16s rDNA test system provided a diagnostic result within 25 minutes in 97% (75 of 77) of all patients. Two samples could not be evaluated due to massive protein precipitation from the synovial sample during the PCR. Other possible confounding factors for sample evaluation, such as variances in synovial viscosity, blood contamination, small sample volumes, or variances in transport times, did not negatively affect the test reliability.

Test performance

ROC analysis in the proof-of-principle cohort revealed an optimal cut-off level of 0.71 AU, between the test and control bands of the 16s rDNA test strip (Fig. 2). Utilizing this cut-off, the 16s rDNA test system was able to detect seven of eight PJI samples and all of the non-PJI samples correctly, achieving a sensitivity of 87.5% and a specificity of 100% (area under the curve (AUC) = 0.944, p = 0.001) in the proof-of-principle cohort (Fig. 2).

General test performance using the proof-of-principle cohort: a) receiver operating characteristic (ROC) curve for the 16s rDNA test based on the calculated ratio between test and control band to determine the optimal cut-off value to differentiate between periprosthetic joint infection (PJI) and non-PJI samples; and b) box-whisker plot displaying the performance of the 16s rDNA test to differentiate between PJI (n = 8) and non-PJI (n = 9) samples in the proof-of-principle cohort. Dashed lines indicate the optimal cut-off as determined by previous ROC analysis. The Mann–Whitney U test was used to obtain p-values. AUC, area under the curve; CI, confidence interval; AU, assay unit.

General test performance using the proof-of-principle cohort: a) receiver operating characteristic (ROC) curve for the 16s rDNA test based on the calculated ratio between test and control band to determine the optimal cut-off value to differentiate between periprosthetic joint infection (PJI) and non-PJI samples; and b) box-whisker plot displaying the performance of the 16s rDNA test to differentiate between PJI (n = 8) and non-PJI (n = 9) samples in the proof-of-principle cohort. Dashed lines indicate the optimal cut-off as determined by previous ROC analysis. The Mann–Whitney U test was used to obtain p-values. AUC, area under the curve; CI, confidence interval; AU, assay unit.

Validation of test performance

Using the predefined cut-off value in the validation cohort, the 16s rDNA test system achieved a sensitivity of 82% (true positive = 18, false negative = 4) and specificity of 89% (true negative = 32, false positive = 4) (AUC = 0.894, p < 0.001). Examination of the ROC curve of the validation cohort confirmed the predetermined cut-off of 0.71 AU as optimal to discriminate between PJI and non-PJI samples (Fig. 3). The performance of the 16s rDNA test was independent of the isolated bacterial species. The complete list of detected bacterial species grouped according to their detection by microbiological culture or 16s rDNA test is displayed in Table III.

Validation of the test performance using the validation cohort: a) receiver operating characteristic (ROC) curve for the 16s rDNA test (ratio between test and control band on the test strip) to differentiate between periprosthetic joint infection (PJI) and non-PJI samples in the validation cohort; and b) box-whisker plot displaying the performance of the 16s rDNA test to differentiate between PJI (n = 23) and non-PJI (n = 37) samples in the validation cohort. Dashed lines indicate the predefined cut-off as determined using the proof-of-principle cohort. The Mann–Whitney U test was used to obtain p-values. AUC, area under the curve; CI, confidence interval; AU, assay unit.

Table III.

Detected bacterial species grouped according to their detection by microbiological culture or 16s rDNA test

Bacterial speciesCulture positive16s rDNA test positive
Staphylococcus epidermidis++
Staphylococcus hominis++
Staphylococcus caprae++
Staphylococcus capitis++
Staphylococcus warneri++
Staphylococcus aureus++
Streptococcus agalactiae++
Propionibacterium acnes++
Enterococcus faecalis++
Enterococcus coli+-
Dermabacter hominis+-
Validation of the test performance using the validation cohort: a) receiver operating characteristic (ROC) curve for the 16s rDNA test (ratio between test and control band on the test strip) to differentiate between periprosthetic joint infection (PJI) and non-PJI samples in the validation cohort; and b) box-whisker plot displaying the performance of the 16s rDNA test to differentiate between PJI (n = 23) and non-PJI (n = 37) samples in the validation cohort. Dashed lines indicate the predefined cut-off as determined using the proof-of-principle cohort. The Mann–Whitney U test was used to obtain p-values. AUC, area under the curve; CI, confidence interval; AU, assay unit. Detected bacterial species grouped according to their detection by microbiological culture or 16s rDNA test

Test performance in comparison with conventional microbiological methods

We directly compared the diagnostic performance of the 16s rDNA test with the individual performance of the conventional microbiological diagnostic methods, comprised of synovial fluid and periprosthetic tissue cultures, as well as the histological evaluation of the periprosthetic membrane. The microbiological culture of synovial fluid achieved a lower sensitivity than that of the 16s rDNA test with 80%, and a specificity of 93%. The combination of synovial fluid and tissue sample cultures achieved a sensitivity of 86% and specificity of 86%. Overall, the correlation between the 16s rDNA test and the microbiological cultures showed a concordance in 75% of all cases, with the 16s rDNA test and the microbiological cultures both being either positive or negative. The correlation between the 16s rDNA test and the histological evaluation of the periprosthetic tissue sample was slightly superior, with a concordance rate of 77%.

Discussion

Despite the longer time period associated with culture-based methods, which precludes an intraoperative application, the detection of PJI by microbiological culture remains the benchmark in PJI diagnostics. To avoid the disadvantages associated with microbiological culture, we developed a test for the rapid detection of bacterial 16s rDNA from synovial fluid (within 25 minutes). To our knowledge, the shortest reported times for the performance of a PCR-based 16s rDNA detection are, in the current literature, three hours and 4.5 hours.[12,17,18] A distinct advantage of the 16s rDNA test over other diagnostic methods, such as leucocyte esterase, is the high degree of reliability and resistance to contamination. The detection of leucocyte esterase from synovial fluid is very susceptible to blood contamination, making an evaluation of up to 17% of all samples impossible.[2] The high degree of reliability of the 16s rDNA test, with 97% of all samples providing a diagnostic result, and the execution within 25 minutes from only 2 µl of synovial fluid, allow for a true intraoperative application. Since total joint arthroplasties release wear particles with heterogeneous physicochemical properties, these could theoretically interfere with our 16s rDNA test. To address this issue and to take the heterogeneity of potential patient cohorts into account, patients undergoing arthroplasty revision, as well as primary arthroplasty, were included in our patient collective. The high degree of correlation between the results of our 16s rDNA test and those of the microbiological culture shows that a reliable detection of PJI from synovial fluid is possible even in the presumed presence of wear particles. Although it was not the primary goal of this study to achieve a superior sensitivity over the standard intraoperative microbiological cultures, the 16s rDNA test achieved a slightly higher sensitivity than both the microbiological culture of synovial fluid and periprosthetic tissue cultures.[30] The differences in sensitivity and specificity of the 16s rDNA test in the proof-of-principle and validation cohorts could be attributed to the differences in sample size and PJI incidence between the cohorts. In addition, the sensitivity of 82% achieved by our synovial fluid 16s rDNA test exceeded the reported sensitivity rates of other 16s rDNA tests which ranged from 64% to 76%.[9-11] The achieved correlation rate and sensitivity are independent of the bacterial species, since the utilized primer sequences match to a highly conservative region of bacterial rDNA encoding the 16s ribosomal subunit, which is identical in prokaryotes.[31] The 16s rDNA test was able to detect all of the bacterial species isolated by microbiological culture, except in two cases (Table I). Only two isolations of E. coli and Dermabacter hominis were not detected. Both cases represent single positive bacterial isolations in two different patients. The isolation of Dermabacter hominis was only present in the SFC, with all other microbiological cultures remaining negative. The isolation of E. coli represented one of the two 16s rDNA tests which were not analyzable due to massive protein precipitation in the synovial fluid sample. Our study also has a number of technical limitations. First, specialized equipment, such as a thermocycler, is necessary for an intraoperative application to perform the 16s rDNA test. Therefore, all samples were transported to our research facility for this study and proof of applicability in a true intraoperative scenario is pending. Nevertheless, the test was developed as a fully automated system with a focus on convenience, user friendliness, and rapid detection to allow for an intraoperative application, without further modifications. The translation of the test system into clinical application is the main goal in the continuation of this project. Second, the small patient cohort, to date, should be supplemented by a larger prospective cohort to confirm and validate our current findings. Third, specific indications, such as a prospective comparison between intraoperative frozen tissue sections and the current 16s rDNA test, should be investigated. Finally, our proposed test system has a restricted ability to distinguish between living and dead bacteria, which potentially limits its use to monitor the infection status after antibiotic treatment. Thus, further studies must be performed to validate our findings in synovial fluid from PJI patients after antibiotic treatment. Previous studies have shown that a pre-incubation of biological samples with the membrane-impermeant agent propidium monoazide prevents the amplification of the 16s rDNA from dead cells; such a modification to our 16s rDNA test could be a promising method to further maximize the clinical utility.[32,33] Furthermore, our 16s rDNA test rapidly detects the presence of bacteria, but does not detect the specific bacterial strain or, more importantly, a potential antibiotic resistance. Thus, we currently aim to extend our 16s rDNA test towards a multiplex approach, allowing for the simultaneous identification of clinically relevant bacterial strains, as well as specific antibiotic-resistant genes. In conclusion, the current system can reliably and rapidly detect PJI, enabling an intraoperative application. The direct detection of bacterial 16s rDNA shows encouraging results, and warrants further evaluation in larger patient cohorts. The future addition of the detection of clinically relevant antibiotic resistance will be a focus of further research.
  32 in total

1.  Role of universal 16S rRNA gene PCR and sequencing in diagnosis of prosthetic joint infection.

Authors:  M Marín; J M Garcia-Lechuz; P Alonso; M Villanueva; L Alcalá; M Gimeno; E Cercenado; M Sánchez-Somolinos; C Radice; E Bouza
Journal:  J Clin Microbiol       Date:  2011-12-14       Impact factor: 5.948

2.  Leukocyte esterase reagent strips for the rapid diagnosis of periprosthetic joint infection.

Authors:  Nathan G Wetters; Keith R Berend; Adolph V Lombardi; Michael J Morris; Tawnya L Tucker; Craig J Della Valle
Journal:  J Arthroplasty       Date:  2012-05-17       Impact factor: 4.757

3.  Simulated joint infection assessment by rapid detection of live bacteria with real-time reverse transcription polymerase chain reaction.

Authors:  Patrick Birmingham; Jeannine M Helm; Paul A Manner; Rocky S Tuan
Journal:  J Bone Joint Surg Am       Date:  2008-03       Impact factor: 5.284

4.  Prosthetic joint infection diagnosis using broad-range PCR of biofilms dislodged from knee and hip arthroplasty surfaces using sonication.

Authors:  Eric Gomez; Charles Cazanave; Scott A Cunningham; Kerryl E Greenwood-Quaintance; James M Steckelberg; James R Uhl; Arlen D Hanssen; Melissa J Karau; Suzannah M Schmidt; Douglas R Osmon; Elie F Berbari; Jayawant Mandrekar; Robin Patel
Journal:  J Clin Microbiol       Date:  2012-08-15       Impact factor: 5.948

Review 5.  Revised histopathological consensus classification of joint implant related pathology.

Authors:  V Krenn; L Morawietz; G Perino; H Kienapfel; R Ascherl; G J Hassenpflug; M Thomsen; P Thomas; M Huber; D Kendoff; D Baumhoer; M G Krukemeyer; S Natu; F Boettner; J Zustin; B Kölbel; W Rüther; J P Kretzer; A Tiemann; A Trampuz; L Frommelt; R Tichilow; S Söder; S Müller; J Parvizi; U Illgner; T Gehrke
Journal:  Pathol Res Pract       Date:  2014-10-17       Impact factor: 3.250

Review 6.  Dead or alive: molecular assessment of microbial viability.

Authors:  Gerard A Cangelosi; John S Meschke
Journal:  Appl Environ Microbiol       Date:  2014-07-18       Impact factor: 4.792

7.  The role of intraoperative frozen sections in revision total joint arthroplasty.

Authors:  D S Feldman; J H Lonner; P Desai; J D Zuckerman
Journal:  J Bone Joint Surg Am       Date:  1995-12       Impact factor: 5.284

8.  Prolonged bacterial culture to identify late periprosthetic joint infection: a promising strategy.

Authors:  Peter Schäfer; Bernd Fink; Dieter Sandow; Andreas Margull; Irina Berger; Lars Frommelt
Journal:  Clin Infect Dis       Date:  2008-12-01       Impact factor: 9.079

Review 9.  Qualifying stem cell sources: how to overcome potential pitfalls in regenerative medicine?

Authors:  Simon Reinke; Anke Dienelt; Antje Blankenstein; Georg N Duda; Sven Geissler
Journal:  J Tissue Eng Regen Med       Date:  2014-06-12       Impact factor: 3.963

10.  Diagnosing periprosthetic joint infection: has the era of the biomarker arrived?

Authors:  Carl Deirmengian; Keith Kardos; Patrick Kilmartin; Alexander Cameron; Kevin Schiller; Javad Parvizi
Journal:  Clin Orthop Relat Res       Date:  2014-11       Impact factor: 4.176

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  8 in total

1.  Improved diagnosis of chronic hip and knee prosthetic joint infection using combined serum and synovial IL-6 tests.

Authors:  Leilei Qin; Xinyu Li; Jiawei Wang; Xuan Gong; Ning Hu; Wei Huang
Journal:  Bone Joint Res       Date:  2020-09-20       Impact factor: 5.853

2.  The value of calprotectin in synovial fluid for the diagnosis of chronic prosthetic joint infection.

Authors:  Zeyu Zhang; Yuanqing Cai; Guochang Bai; Chaofan Zhang; Wenbo Li; Bin Yang; Wenming Zhang
Journal:  Bone Joint Res       Date:  2020-08-11       Impact factor: 5.853

3.  COVID-19: potential transmission through aerosols in surgical procedures and blood products.

Authors:  A Hamish R W Simpson; Graham Dall; Jürgen G Haas
Journal:  Bone Joint Res       Date:  2020-07-23       Impact factor: 5.853

4.  Detecting the presence of bacterial RNA by polymerase chain reaction in low volumes of preoperatively aspirated synovial fluid from prosthetic joint infections.

Authors:  B Yang; X Fang; Y Cai; Z Yu; W Li; C Zhang; Z Huang; W Zhang
Journal:  Bone Joint Res       Date:  2020-06-08       Impact factor: 5.853

5.  Rapid analysis of bacterial composition in prosthetic joint infection by 16S rRNA metagenomic sequencing.

Authors:  Mei-Feng Chen; Chih-Hsiang Chang; Chuan Chiang-Ni; Pang-Hsin Hsieh; Hsin-Nung Shih; Steve W N Ueng; Yuhan Chang
Journal:  Bone Joint Res       Date:  2019-09-03       Impact factor: 5.853

6.  A sophisticated antibiotic-loading protocol in articulating cement spacers for the treatment of prosthetic joint infection: A retrospective cohort study.

Authors:  Chuang Yang; Jin Wang; Zhifei Yin; Qiaojie Wang; Xianlong Zhang; Yao Jiang; Hao Shen
Journal:  Bone Joint Res       Date:  2019-12-03       Impact factor: 5.853

7.  Diagnosis of Metal Hypersensitivity in Total Knee Arthroplasty: A Case Report.

Authors:  Janosch Schoon; Melanie J Ort; Katrin Huesker; Sven Geissler; Anastasia Rakow
Journal:  Front Immunol       Date:  2019-11-27       Impact factor: 7.561

8.  Diagnostic validation of a rapid and field-applicable PCR-lateral flow test system for point-of-care detection of cyprinid herpesvirus 3 (CyHV-3).

Authors:  Finn N Loose; André Breitbach; Ivo Bertalan; Dana Rüster; Uwe Truyen; Stephanie Speck
Journal:  PLoS One       Date:  2020-10-30       Impact factor: 3.240

  8 in total

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