Skip to main content
Download PDF

Evaluation of GeneXpert EV assay for the rapid diagnosis of enteroviral meningitis: a systematic review and meta-analysis

Annals of Clinical Microbiology and Antimicrobials volume 21, Article number: 25 (2022) Cite this article

Abstract

Background

GeneXpert enterovirus Assay is a PCR-based assay for Enterovirus meningitis diagnosis. However, there is currently no research about the performance of GeneXpert enterovirus assay in the diagnosis of enterovirus meningitis. Thus, a systematic review and meta-analysis is significant on the topic.

Methods

Embase, Cochrane Library, Web of Science, and PubMed were systematically reviewed with retrieval types. Some criteria were used to filter the studies. Only studies published in English, that made a comparison between GeneXpert enterovirus assay and RT-PCR, and could be formulated in a 2*2 table, were included. The quality of the included studies was evaluated by QUADAS-2. The effect of the GeneXpert enterovirus assay was assessed by the Sensitivity, Specificity, Positive Likelihood Ratio, Negative Likelihood Ratio, Diagnosis Odds Ratio, and summary receiver operating characteristic (SROC) curve. Publication bias and heterogeneity were evaluated by the Deeks' funnel test and Bivariate Box plot respectively.

Results

7 studies were recruited in the analysis. The Pooled Sensitivity was 0.96 [95% CI (0.94–0.97)], Pooled Specificity was 0.99 [95% CI (0.98–0.99)], Positive Likelihood Ratio was 130.46 [95% CI (35.79–475.58)], Negative Likelihood Ratio was 0.04 [95% CI (0.02–0.10)], and Diagnostic Odds Ratio was 3648.23 (95% CI [963.99–13,806.72)]. In SROC Curve, Area Under Curve (AUC) was 0.9980, and Q*= 0.9849. In Deeks' funnel test, the P-value was 0.807 (P > 0.05), indicating no publication bias. The Bivariate Box plot indicated no evident heterogeneity.

Conclusions

The GeneXpert enterovirus assay demonstrated high diagnostic accuracy in diagnosing enterovirus meningitis.

Introduction

The Enterovirus genus is one of the most populous in the family Picornaviridae [1], in which, human Enteroviruses (Human EVs) have been discovered with more than 250 subtypes and with a diameter between 28 and 30 nm [2]. Meningitis contains bacterial meningitis and aseptic meningitis. As one of aseptic meningitis, which is infected by an enterovirus, [3] Enterovirus meningitisis the most common non-bacterial meningitis and accounts for 90% in children and adults. However, no antiviral drugs have been approved for the treatment of EV infections [4]. In addition, most patients with enterovirus meningitis have no obvious symptoms after infection, with only less than 10 percent of patients behave obvious symptoms and can receive treatment timely [2]. If it is hard to quickly and accurately diagnose whether it's enterovirus meningitis, patients might receive unnecessary treatment or hospitalization [5, 6]. Therefore, simple and reliable methods of identifying patients whether infected with enterovirus meningitis are critical to the clinic.

Nucleic acid amplification methods (NAATs) are widely used in the diagnosis of enterovirus meningitis [7]. The real-time polymerase chain reaction (RT-PCR) is a kind of NAATs. In 2003, the World Health Organization (WHO) announced the adoption of RT-PCR to detect enteroviruses meningitis. Compared with the traditional viral culture [8, 9], RT-PCR can make a diagnosis within a shorter time of 7 h, and with higher sensitivity and specificity (approximately 100%) [10, 11]. Nowadays, RT-PCR is considered the gold standard for the diagnosis and identification of enterovirus meningitis [12]. But RT-PCR assay has two evident limitations. On the one hand, it is too expensive and couldn’t be applied in budget-limited rural clinics in some regions. On the other hand, when detecting CSF samples from low viral load level, like the early phase of infection, its sensitivity is too low to detecting enteroviruses meningitis [13, 14].

The GeneXpert EV assay (GXEA, Cepheid, Sunnyvale, CA) is a fully integrated automated nucleic acid sample preparation system that consists of instruments, computers, and disposable fluid boxes [9], with a diagnostic turnaround time of 2.5 h [15]. What’s more, because its test box is completely independent and could conduct all the procedures, there is less FP in GeneXpert EV Assay in the diagnosis of enteroviral meningitis [9, 16]. However, so far, there is no comprehensive and systematic study for GeneXpert EV assay. Thus, in the present work, we conducted a systematic review and meta-analysis to explore the diagnostic accuracy of GeneXpert EV assay in enteroviral meningitis.

Methods

Search methods

Original studies published in English from the establishment of the databases to January 30, 2021, were searched on PubMed, Embase, Cochrane Library, and Web of Science by two researchers (ML, YRL) independently. In addition, the references of the included literature and unpublished literature were hand-searched by two researchers (JQL, ML) to make sure all the relevant articles are covered. Discrepancies were resolved by discussion among all the researchers. The MeSH terms and search strategies are reported in (Additional file 1): appendix S1.

Study selection

All researchers have received prior training in systematic reviews and meta-analysis. The Kappa test was used to assess the agreement among the results given by the researchers. 50 citations are selected randomly to screen and calculate the Kappa value. If Kappa was less than 0.75, the second round of training will be carried out. Titles and abstracts are screened by two researchers independently (YWC, XJC). The screening of full texts will be screened by two other researchers (ML, GYW). Disagreements were resolved by consensus of all researchers. Overall, studies eligible for inclusion met all of the following criteria: (1) Published in English; (2) GeneXpert EV assay as an index text; (3) RT-PCR as the reference standard; (4) Data in studies could be formed a 2*2 table. The criteria for exclusion were as follows: (1) Non-English pieces of literature; (2) The index text was no GeneXpert EV assay; (3) The reference standard was no RT-PCR; (4) The article data was not enough to formulate the 2*2 table; (5) Studies included conference abstracts or reviews were also excluded. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISM) was used to describe the steps of the study selection in the systematic review and meta-analysis.

Data extraction

The name of the first author, year of publication, country, experiment type (prospective or retrospective), the source and quantity of samples, patient's age and gender, index test, gold standard, true-positive (TP), false-positive (FP), true-negative (TN) and false-negative (FN) were extracted from each included study. Due to the limitation of datasets, the classification of RT-PCR couldn’t be extracted from the included studies. Data were extracted by 7 researchers of the study team (ML, YRL, GYW, QWL, WHY, YPL, and JQL) independently. They were blinded to each other’s results. Disagreements were resolved by consensus.

Quality assessment

Quality assessment of each article was conducted independently by 6 researchers (ML, YRL, JQL, YWC, XJC, YPL) according to the Quality Assessment of Studies of Diagnostic Accuracy included in Systematic Reviews-2 (QUADAS-2) [17]. The QUADAS-2 includes 4 parts: indicator testing, reference criteria, patient selection, and process and time. And each section could be considered as high, unclear, or low risk of bias independently. All analyses were done with Excel and Review Manager 5.3.0 (The Cochrane Collaboration, Copenhagen, Denmark). Disagreements will be discussed and decided by the above 6 researchers.

Statistical analysis

The Meta-Disc [18] was applied to analyze the pooled sensitivity, pooled specificity, diagnostic positive likelihood ratio (+ LR), diagnostic negative LR (-LR), diagnostic odds ratio (DOR), and SROC curve with all the 95% confidence intervals (95% CI). The publication bias of sensitivity and specificity in the included studies was analyzed in Stata12.0 with Deeks’ funnel plot. In addition, heterogeneity was evaluated according to the Bivariate Box plot by using Stata12.0. In the end, the table checklist of this systematic review and meta-analysis could be found in Additional file 2.

Results

Eligible studies after systematic review

36 citations were obtained totally, including 33 citations from the systematic review, and 3 citations from hand-searched. According to the inclusion and exclusion items, 7 citations were left [12, 16, 19,20,21,22]. In Katja Seme’s work, preliminary results were obtained by using RT-PCR and GeneXpert EV assay detection. However, due to invalid results existing (preliminary negative and uncertain), the authors reexamined and obtained the final results [19]. Thus, the datasets from Katja Seme were divided into two 2*2 tables. The search process and results according to PRISMA 2009 Flow Diagram are outlined in Additional file 3.

Study characteristics of the included studies

In all included studies, 2 articles were retrospective [21], and 1 article was both retrospective and prospective [16], only 4 articles provided the ages of the patients clearly [12, 16, 20, 21]. All the studies did not use platforms. The characteristics were summarized in Table 1.

Table 1 Summary of the characteristics of included studies
Full size table

Quality assessment of the included studies according to QUADAS-2

In Patient Selection, all the studies were considered as low risk of bias. In Index Text, 2 articles were considered as unclear risk of bias because the results of the gold standard and index test were given at the same time; 4 articles were likely to have a high risk of bias because the results of the index test were not carried out without knowing the results of the gold standard. In Reference Standard, 2 studies were likely to have an unclear risk and a high risk of bias, respectively. In Flow and Timing, all studies were likely to have a low risk of bias. The results were plotted in Fig. 1.

Fig. 1
figure 1

Risk of bias and applicability concerns graph

Full size image

Diagnostic accuracy of expert EV assay for enteroviral meningitis

The Pooled Sensitivity (A) was 0.96 [95% CI (0.94–0.97)], Pooled Specificity(B) was 0.99 [95% CI (0.98 – 0.99)], Pooled Positive LR (C) was 130.46 [95% CI (35.79–475.58)], Pooled Negative LR (D) was 0.04 [95% CI (0.02–0.10)], and Pooled Diagnostic Odds Ratio was 3648.23 (95% CI [963.99–13,806.72)] (Figs. 2A–D, 3.)

Fig. 2
figure 2

Sensitivity (A), specificity (B), PLR (C) and NLR (D)

Full size image
Fig. 3
figure 3

Diagnostic Odds Ratio (DOR)

Full size image

SROC curve of Xpert EV assay for enteroviral meningitis

In SROC Curve (Fig. 4.), AUC was 0.9980, Q index was 0.9849. Both results were close to 1, indicating the high accuracy of the GeneXpert EV in the diagnosis of enteroviral meningitis.

Fig. 4
figure 4

SROC Curve

Full size image

Publication bias of the included studies

Deeks' funnel plot test was conducted to evaluate the publication bias. In the results, most of the points are symmetrical and the P-value was 0.807 (P > 0.05), indicating that no publication bias exists [23]. The Deeks' funnel plot result could be sought in Fig. 5A.

Fig. 5
figure 5

Deeks' funnel plot (A) and Bivariate box plot (B)

Full size image

Heterogeneity analysis

The Bivariate Box plot shows no evident heterogeneity among the included studies (Fig. 5B). The Pooled Diagnostic Odds Ratio shows no significant heterogeneity through the random-effects model (I2 = 45.9% < 50%, Cochran-Q = 12.93, Fig. 3).

Discussion

In this systematic review and meta-analysis, we evaluated the GeneXpert EV assay in the diagnosis of enterovirus meningitis. On the one hand, the results demonstrate that GeneXpert EV assay has high sensitivity and specificity, although one outlier exists with a lower sensitivity of 0.82 [95% CI (0.66–0.92)]. The outlier may cause by the two-step PT-PCR, which was considered with a higher diagnosis performance than one-step RT-PCR [21]. In Positive LR, a numerical value is lower than others {22.02 [95% CI (13.17–36.82)]}. The lower value can be explained by intricate operations of the equipment with the assumption of FP results may not cause by a target and amplicon cross-contamination [16].

On the other hand, no evident heterogeneity exists in the Bivariate Box plot. In addition, there was no curve pattern (shoulder-arm pattern) in the SROC Curve [18], indicating no evident heterogeneity. Furthermore, the inconsistency was 45.9% in the frost plot of Diagnostic Odds Ratio, which proved the above results once again. However, the inconsistency was 78.8% in the frost plot of Sensitivity, which was prompting the high heterogeneity in the study. Thus, we explored the sources of the heterogeneity: First, the lower sensitivity in the GeneXpert EV assay may be a result of lacking a 1:5 sample dilution of CSF in saline, or freezing and thawing the undiluted CSF [24]. Second, the performance of the GeneXpert EV assay may be influenced by the different lumbar puncture practices in different regions [19]. Unfortunately, since the lack of information, we couldn’t extract this data from included studies.

Undoubtedly, some advantages are represented in the GeneXpert EV assay. First, since the GeneXpert EV assay cartridge is completely self-contained and performs all assay steps including sample preparation, the false positive due to cross-contamination could be avoided. Second, the GeneXpert EV assay is robust and not prone to operator error [16, 19]. Third, reliable results could be obtained rapidly (only 2.5 h) within the spinal fluid collection when using GeneXpert EV assay [25]. Fourth, the GeneXpert EV assay is a fully automatic method, that could be operated easily that specially trained laboratory staff were not required [16].

There are several drawbacks to this systematic review. On the one hand, we only brought English studies into consideration in our study, omitting studies in different languages. On the other hand, there were only 8 sets of data in this analysis due to the insufficiency of qualified studies. Besides, we failed to extract part of the data due to the limitation of data sources.

Conclusions

In general, the GeneXpert EV assay in diagnosing enteroviral meningitis has been further studied through systematic review and meta-analysis in this work. The results demonstrate that the GeneXpert EV assay has shown good performance in the diagnosis of enterovirus meningitis. As a supplementary method for enterovirus meningitis diagnosis, the GeneXpert EV assay is worthy to be popularized in clinical practice. However, more clinical studies are needed to further explore its role in different viral loads and different patients.

Availability of data and materials

All data analyzed in this study are included in the article.

Abbreviations

EV:

Enteroviral

QUADAS:

Quality assessment of diagnostic accuracy studies

NLR:

Negative likelihood ratio

PLR:

Positive likelihood ratio

CI:

Confidence interval

DOR:

Diagnostic odds ratio

SROC:

Summary receiver operating characteristic

AUC:

Area under the curve

References

  1. Wang K, Zheng B, Zhang L, Cui L, Su X, Zhang Q, Guo Z, Guo Y, Zhang W, Zhu L, et al. Serotype specific epitopes identified by neutralizing antibodies underpin immunogenic differences in Enterovirus B. Nat Commun. 2020;11(1):4419.

    Article  CAS  Google Scholar 

  2. Faleye TO, Adewumi MO, Adeniji JA. Defining the enterovirus diversity landscape of a fecal sample: a methodological challenge? Viruses. 2016. https://doi.org/10.3390/v8010018.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Laitinen OH, Svedin E, Kapell S, Nurminen A, Hytönen VP, Flodström-Tullberg M. Enteroviral proteases: structure, host interactions, and pathogenicity. Rev Med Virol. 2016;26(4):251–67.

    Article  Google Scholar 

  4. de Crom SC, Rossen JW, van Furth AM, Obihara CC. Enterovirus and parechovirus infection in children: a brief overview. Eur J Pediatr. 2016;175(8):1023–9.

    Article  Google Scholar 

  5. Tunkel AR, Hartman BJ, Kaplan SL, Kaufman BA, Roos KL, Scheld WM, Whitley RJ. Practice guidelines for the management of bacterial meningitis. Clin Infect Dis. 2004;39(9):1267–84.

    Article  Google Scholar 

  6. Archimbaud C, Chambon M, Bailly JL, Petit I, Henquell C, Mirand A, Aublet-Cuvelier B, Ughetto S, Beytout J, Clavelou P, et al. Impact of rapid enterovirus molecular diagnosis on the management of infants, children, and adults with aseptic meningitis. J Med Virol. 2009;81(1):42–8.

    Article  CAS  Google Scholar 

  7. Capaul SE, Gorgievski-Hrisoho M. Detection of enterovirus RNA in cerebrospinal fluid (CSF) using NucliSens EasyQ Enterovirus assay. J Clin Virol. 2005;32(3):236–40.

    Article  CAS  Google Scholar 

  8. Noordhoek GT, Weel JF, Poelstra E, Hooghiemstra M, Brandenburg AH. Clinical validation of a new real-time PCR assay for detection of enteroviruses and parechoviruses, and implications for diagnostic procedures. J Clin virol. 2008;41(2):75–80.

    Article  CAS  Google Scholar 

  9. Kost CB, Rogers B, Oberste MS, Robinson C, Eaves BL, Leos K, Danielson S, Satya M, Weir F, Nolte FS. Multicenter beta trial of the GeneXpert enterovirus assay. J Clin Microbiol. 2007;45(4):1081–6.

    Article  CAS  Google Scholar 

  10. Menasalvas-Ruiz AI, Salvador-García C, Moreno-Docón A, Alfayate-Miguélez S, Pérez Cánovas C, Sánchez-Solís M. Enterovirus reverse transcriptase polymerase chain reaction assay in cerebrospinal fluid: An essential tool in meningitis management in childhood. Enferm Infecc Microbiol Clin. 2013;31(2):71–5.

    Article  Google Scholar 

  11. Piqueur MA, Verstrepen WA, Bruynseels P, Mertens AH. Improvement of a real-time RT-PCR assay for the detection of enterovirus RNA. Virology journal. 2009;6:95.

    Article  Google Scholar 

  12. Ninove L, Nougairede A, Gazin C, Zandotti C, Drancourt M, de Lamballerie X, Charrel RN. Comparative detection of enterovirus RNA in cerebrospinal fluid: GeneXpert system vs. real-time RT-PCR assay. Clin Microbiol Infect. 2011;17(12):1890–4.

    Article  CAS  Google Scholar 

  13. Tan EL, Chow VT, Kumarasinghe G, Lin RT, Mackay IM, Sloots TP, Poh CL. Specific detection of enterovirus 71 directly from clinical specimens using real-time RT-PCR hybridization probe assay. Mol Cell Probes. 2006;20(2):135–40.

    Article  CAS  Google Scholar 

  14. Niu P, Qi S, Yu B, Zhang C, Wang J, Li Q, Ma X. Development of a highly sensitive real-time nested RT-PCR assay in a single closed tube for detection of enterovirus 71 in hand, foot, and mouth disease. Adv Virol. 2016;161(11):3003–10.

    CAS  Google Scholar 

  15. Marlowe EM, Novak SM, Dunn JJ, Smith A, Cumpio J, Makalintal E, Barnes D, Burchette RJ. Performance of the GeneXpert enterovirus assay for detection of enteroviral RNA in cerebrospinal fluid. J clin virol. 2008;43(1):110–3.

    Article  CAS  Google Scholar 

  16. Nolte FS, Rogers BB, Tang YW, Oberste MS, Robinson CC, Kehl KS, Rand KA, Rotbart HA, Romero JR, Nyquist AC, et al. Evaluation of a rapid and completely automated real-time reverse transcriptase PCR assay for diagnosis of enteroviral meningitis. J Clin Microbiol. 2011;49(2):528–33.

    Article  Google Scholar 

  17. Whiting PF, Rutjes AW, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, Leeflang MM, Sterne JA, Bossuyt PM. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529–36.

    Article  Google Scholar 

  18. Zamora J, Abraira V, Muriel A, Khan K, Coomarasamy A. Meta-DiSc: a software for meta-analysis of test accuracy data. BMC Med Res Methodol. 2006;6:31.

    Article  Google Scholar 

  19. Seme K, Mocilnik T, Komlos KF, Doplihar A, Persing DH, Poljak M. GeneXpert enterovirus assay: one-year experience in a routine laboratory setting and evaluation on three proficiency panels. J Clin Microbiol. 2008;46(4):1510–3.

    Article  Google Scholar 

  20. Ninove L, Nougairede A, Gazin C, Zandotti C, Drancourt M, de Lamballerie X, Charrel RN. POC tests: from antigen detection to molecular methods. Future trends. J Clin Virol. 2010;49(4):304–5.

    Article  Google Scholar 

  21. de Crom SC, Obihara CC, van Loon AM, Argilagos-Alvarez AA, Peeters MF, van Furth AM, Rossen JW. Detection of enterovirus RNA in cerebrospinal fluid: comparison of two molecular assays. J Virol Methods. 2012;179(1):104–7.

    Article  Google Scholar 

  22. Slika S, Abbas F, Mahfouz R. Implementation of the cepheid xpert EV assay for rapid detection of enteroviral meningitis: experience of a tertiary care center and a technical review. Genet Test Mol Biomarkers. 2013;17(3):232–5.

    Article  Google Scholar 

  23. Deeks JJ, Higgins JPT, Altman DG. Analysing data and undertaking meta-analyses. In: Higgins JPT, Green S, editors. Cochrane Handbook for systematic reviews of interventions. Chichester: John Wiley & Sons, Ltd; 2008. p. 243–96.

    Chapter  Google Scholar 

  24. Sefers SE, Raymer AK, Kilby JT, Persing DH, Tang YW. Prevalence and management of invalid GeneXpert enterovirus results obtained with cerebrospinal fluid samples: a 2-year study. J Clin Microbiol. 2009;47(9):3008–10.

    Article  Google Scholar 

  25. Hong J, Kim A, Hwang S, Cheon DS, Kim JH, Lee JW, Park JH, Kang B. Comparison of the genexpert enterovirus assay (GXEA) with real-time one step RT-PCR for the detection of enteroviral RNA in the cerebrospinal fluid of patients with meningitis. Virol J. 2015;12:27.

    Article  Google Scholar 

Download references

Acknowledgements

We express our sincere gratitude to all the patients and clinical researchers who were involved in the included studies for their wonderful work and valuable participation.

Funding

No funding was used to support this study.

Author information

Authors and Affiliations

  1. Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China

    Min Lin & Xu-Guang Guo

  2. Department of Chinese and Western Medicine in Clinical Medicine, The Clinical School of Chinese and Western Medicine, Guangzhou Medical University, Guangzhou, 511436, China

    Min Lin, Yun-Ran Li, Jia-Qi Liu, Ying-Wen Chen & Ge-Yuan Wu

  3. Department of Medical Imageology, The Second Clinical School of Guangzhou Medical University, Guangzhou, 511436, China

    Qi-Wen Lan

  4. Department of Medical Laboratory Technology, The KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, 511436, China

    Li-Jun Long

  5. Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou, 511436, China

    Xun-Jie Cao & Xu-Guang Guo

  6. Department of Clinical Medicine, The Second Clinical School of Guangzhou Medical University, Guangzhou, 511436, China

    Ya-Ping Li

  7. Key Laboratory for Major Obstetric Diseases of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China

    Xu-Guang Guo

  8. Department of Laboratory Medicine, Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510150, China

    Xu-Guang Guo

Authors
  1. Min Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yun-Ran Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qi-Wen Lan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Li-Jun Long
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jia-Qi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ying-Wen Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xun-Jie Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ge-Yuan Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ya-Ping Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Xu-Guang Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

ML, YRL, JQL, XJC, YWC, YPL, GYW, and XGG conceived and designed the experiments. ML, YRL, XJC, YWC, GYW, and JQL analyzed the studies and extracted data. ML and YRL contributed to making tables. ML, YRL, LJL, JQL, YPL, GYW, QWL and contributed to the production of figures. All authors participated in the writing, reading, and revision of the manuscript and approved the final version of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Xu-Guang Guo.

Ethics declarations

Ethical approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: S1.

Search terms and search strategy.

Additional file 2: S2.

Table Checklist of this systematic review and meta-analysis.

Additional file 3: S3.

Screening processes.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, M., Li, YR., Lan, QW. et al. Evaluation of GeneXpert EV assay for the rapid diagnosis of enteroviral meningitis: a systematic review and meta-analysis. Ann Clin Microbiol Antimicrob 21, 25 (2022). https://doi.org/10.1186/s12941-022-00517-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12941-022-00517-3

Keywords

Annals of Clinical Microbiology and Antimicrobials

ISSN: 1476-0711

Contact us