Evidence map›Paper›PMID 38435775›Full record

ArticleIranian journal of public health2023

Comparison of Circulating Variants during the Beginning, Middle and the End of the 4th Wave of COVID-19 in Tehran Province, Iran in 2021.

Akram Sadat Ahmadi, Nazanin Zahra Shafiei-Jandaghi, Kaveh Sadeghi, Ahmad Nejati, Sevrin Zadheidar, Talat Mokhtari-Azad, Jila Yavarian

Open access · goldAbstract read
In one paragraph

Article in Iranian journal of public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 45% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 1 institution in 1 country.

Akram Sadat AhmadiDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Nazanin Zahra Shafiei-JandaghiDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Kaveh SadeghiDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Ahmad NejatiDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Sevrin ZadheidarDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Talat Mokhtari-AzadDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Jila YavarianDepartment of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Tehran University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Whole viral genome sequencing with next generation sequencing (NGS) technique is useful tool for determining the diversity of variants and mutations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study we have attempted to characterize the mutations and circulating variants of the SARSCoV-2 genome during the 4 Methods: We performed complete genome sequencing of 15 SARS-CoV-2 detected from 15 COVID-19 patients during the 4 Results: We detected alpha and delta variants during the 4 Conclusion: The detection of the virus mutations is a useful procedure for identifying the virus behavior and its genetic evolution in order to improve the efficacy of the monitoring strategies and therapeutic measures.

Indexed as

COVID-19Genome sequencingMutationSARS-CoV-2Variant

Identifiers

PMID38435775
PMCPMC10903313
OpenAlexW4389516218

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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.