期刊
JOURNAL OF CLINICAL VIROLOGY
卷 101, 期 -, 页码 11-17出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jcv.2018.01.008
关键词
Enterovirus; Detection; EV typing; Neurological infection; European non-polio enterovirus network (ENPEN); Diagnostics
类别
资金
- Quadram Institute [HPRU-201210038]
- European Society for Clinical Virology (ESCV)
- Quadram Institute [HPRU-201210038]
- European Society for Clinical Virology (ESCV)
- MRC [MR/R015600/1] Funding Source: UKRI
Enteroviruses (EV) can cause severe neurological and respiratory infections, and occasionally lead to devastating outbreaks as previously demonstrated with EV-A71 and EV-D68 in Europe. However, these infections are still often underdiagnosed and EV typing data is not currently collected at European level. In order to improve EV diagnostics, collate data on severe EV infections and monitor the circulation of EV types, we have established European non-polio enterovirus network (ENPEN). First task of this cross-border network has been to ensure prompt and adequate diagnosis of these infections in Europe, and hence we present recommendations for nonpolio EV detection and typing based on the consensus view of this multidisciplinary team including experts from over 20 European countries. We recommend that respiratory and stool samples in addition to cerebrospinal fluid (CSF) and blood samples are submitted for EV testing from patients with suspected neurological infections. This is vital since viruses like EV-D68 are rarely detectable in CSF or stool samples. Furthermore, reverse transcriptase PCR (RT-PCR) targeting the 5' noncoding regions (5' NCR) should be used for diagnosis of EVs due to their sensitivity, specificity and short turnaround time. Sequencing of the VP1 capsid protein gene is recommended for EV typing; EV typing cannot be based on the 5' NCR sequences due to frequent recombination events and should not rely on virus isolation. Effective and standardized laboratory diagnostics and characterisation of circulating virus strains are the first step towards effective and continuous surveillance activities, which in turn will be used to provide better estimation on EV disease burden.
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