Evidence map›Paper›PMID 29445548›Full record

ArticleJournal of pathogens2017

Comparison of Algorithms for the Detection of Enteroviruses in Stool Specimens from Children Diagnosed with Acute Flaccid Paralysis.

J A Adeniji, F A Ayeni, A Ibrahim, K A Tijani, T O C Faleye, M O Adewumi

Abstract read
In one paragraph

Article in Journal of pathogens, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

J A AdenijiDepartment of Virology, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
F A AyeniDepartment of Virology, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
A IbrahimDepartment of Virology, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
K A TijaniDepartment of Virology, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.
T O C FaleyeDepartment of Virology, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.ORCID 0000-0001-7706-9493
M O AdewumiDepartment of Virology, College of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria.ORCID 0000-0002-5172-5808

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was designed to compare both the cell culture dependent and independent enterovirus detection algorithms recommended by the WHO and assess how either might impact our perception of the diversity of enterovirus types present in a sample. Sixteen paired samples (16 isolates from RD cell culture and their corresponding stool suspension, i.e., 32 samples) from AFP cases in Nigeria were analyzed in this study. All the samples were subjected to RNA extraction, cDNA synthesis, the WHO recommended RT-snPCR, and its modification. Amplicons were sequenced and strains identified. Enterovirus diversity was the same between the isolates and fecal suspension for the control and five of the samples. It was, however, different for the remaining 10 (62.5%) samples. Nine (CV-B4, E6, E7, E13, E14, E19, E29, EV-B75, and EV-B77) and five (CV-A1, CV-A11, CV-A13, EV-C99, and PV2) EV-B and EV-C types, respectively, were detected. Particularly, E19 and EV-B75 were only recovered from the isolates while E14, EV-B77, CV-A11, and CV-A13 were only recovered from fecal suspension. Both the cell culture dependent and independent protocols bias our perception of the diversity of enterovirus types present in a sample. Hence, effort should be directed at harmonizing both for increased sensitivity.

Identifiers

PMID29445548
PMCPMC5763071

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.