Evidence map›Paper›PMID 29564068›Full record

ArticleGastroenterology and hepatology from bed to bench2018

Molecular diagnosis of strongyloidiasis in a population of an endemic area through nested-PCR.

Meysam Sharifdini, Amir Keyhani, Mohammad Reza Eshraghian, Eshrat Beigom Kia

Open access · greenAbstract read
In one paragraph

Article in Gastroenterology and hepatology from bed to bench, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.1field-weighted citation impact, top 28% of its field
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

9 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Molecular Characterization ofArchives of Razi Institute · 2024
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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

4 authors at 2 institutions in 1 country.

Meysam SharifdiniDepartment of Medical Parasitology and Mycology, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
Amir KeyhaniDepartment of Medical Parasitology and Mycology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mohammad Reza EshraghianDepartment of Biostatistics and Epidemiology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Eshrat Beigom KiaDepartment of Medical Parasitology and Mycology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Tehran University of Medical Sciences · IRGuilan University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThis study is aimed to diagnose and analyze strongyloidiasis in a population of an endemic area of Iran using nested-PCR, coupled with parasitological methods.

backgroundScreening of strongyloidiasis infected people using reliable diagnostic techniques are essential to decrease the mortality and morbidity associated with this infection. Molecular methods have been proved to be highly sensitive and specific for detection of

methodsA total of 155 fresh single stool samples were randomly collected from residents of north and northwest of Khouzestan Province, Iran. All samples were examined by parasitological methods including formalin-ether concentration and nutrient agar plate culture, and molecular method of nested-PCR. Infections with

resultsBased on the results of nested-PCR method 15 cases (9.7%) were strongyloidiasis positive. Nested-PCR was more sensitive than parasitological techniques on single stool sampling. Elderly was the most important population index for higher infectivity with

conclusionIn endemic areas of

Indexed as

elderlymolecular diagnosisnested-PCRStrongyloides stercoralis

Identifiers

PMID29564068
PMCPMC5849121
OpenAlexW2802954205

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.