Evidence map›Paper›PMID 33762831›Full record

ReviewInfection and drug resistance2021

COVID-19 Pandemic: Review of Contemporary and Forthcoming Detection Tools.

Mumtarin Jannat Oishee, Tamanna Ali, Nowshin Jahan, Shahad Saif Khandker, Md Ahsanul Haq, Mohib Ullah Khondoker, Bijon Kumar Sil, Halyna Lugova, Ambigga Krishnapillai, Abdullahi Rabiu Abubakar and 4 more

Open access · goldAbstract readReview
In one paragraph

Review in Infection and drug resistance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.9field-weighted citation impact, top 7% 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

27 citing papers in PubMed, 47 citations in OpenAlex.

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  13. Rapid detection of SARS-CoV-2: The gradual boom of lateral flow immunoassay.Frontiers in bioengineering and biotechnology · 2022
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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

14 authors at 6 institutions in 3 countries.

Mumtarin Jannat OisheeGonoshasthaya-RNA Molecular Diagnostic and Research Center, Dhaka, Bangladesh.ORCID 0000-0001-5101-9930
Tamanna AliGonoshasthaya-RNA Molecular Diagnostic and Research Center, Dhaka, Bangladesh.ORCID 0000-0001-9139-6095
Nowshin JahanGonoshasthaya-RNA Molecular Diagnostic and Research Center, Dhaka, Bangladesh.ORCID 0000-0001-6507-7031
Shahad Saif KhandkerGonoshasthaya-RNA Molecular Diagnostic and Research Center, Dhaka, Bangladesh.ORCID 0000-0003-4724-0645
Md Ahsanul HaqGonoshasthaya-RNA Molecular Diagnostic and Research Center, Dhaka, Bangladesh.ORCID 0000-0002-4408-6104
Mohib Ullah KhondokerGonoshasthaya Samaj Vittik Medical College, Dhaka, 1344, Bangladesh.ORCID 0000-0003-1021-4435
Bijon Kumar SilGono Bishwabidyalay, Dhaka, 1344, Bangladesh.ORCID 0000-0002-2777-8387
Halyna LugovaFaculty of Medicine and Defence Health, National Defence University of Malaysia, Kuala Lumpur, Malaysia.ORCID 0000-0001-8052-0580
Ambigga KrishnapillaiFaculty of Medicine and Defence Health, National Defence University of Malaysia, Kuala Lumpur, Malaysia.ORCID 0000-0003-3485-2079
Abdullahi Rabiu AbubakarDepartment of Pharmacology and Therapeutics, Faculty of Pharmaceutical Sciences, Bayero University, Kano, 700233, Kano, Nigeria.ORCID 0000-0002-9740-7856
Santosh KumarDepartment of Periodontology and Implantology, Karnavati University, Gandhinagar, 382422, India.ORCID 0000-0002-5117-7872
Mainul HaqueThe Unit of Pharmacology, Faculty of Medicine and Defence Health Universiti Pertahanan, Nasional Malaysia (National Defence University of Malaysia), Kuala Lumpur, Malaysia.ORCID 0000-0002-6124-7993
Mohd Raeed JamiruddinDepartment of Pharmacy, BRAC University, Dhaka, 1212, Bangladesh.ORCID 0000-0003-0495-4808
Nihad AdnanDepartment of Microbiology, Jahangirnagar University, Dhaka, 1342, Bangladesh.ORCID 0000-0002-4999-4793
Gono University · BDNational Defence University of Malaysia · MYBayero University Kano · NGBRAC University · BDJahangirnagar University · BDKarnavati University

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent severe acute respiratory syndrome 2 (SARS-CoV-2) known as COVID-19, presents a deadly challenge to the global healthcare system of developing and developed countries, exposing the limitations of health facilities preparedness for emerging infectious disease pandemic. Opportune detection, confinement, and early treatment of infected cases present the first step in combating COVID-19. In this review, we elaborate on various COVID-19 diagnostic tools that are available or under investigation. Consequently, cell culture, followed by an indirect fluorescent antibody, is one of the most accurate methods for detecting SARS-CoV-2 infection. However, restrictions imposed by the regulatory authorities prevented its general use and implementation. Diagnosis via radiologic imaging and reverse transcriptase PCR assay is frequently employed, considered as standard procedures, whereas isothermal amplification methods are currently on the verge of clinical introduction. Notably, techniques such as CRISPR-Cas and microfluidics have added new dimensions to the SARS-CoV-2 diagnosis. Furthermore, commonly used immunoassays such as enzyme-linked immunosorbent assay (ELISA), lateral flow immunoassay (LFIA), neutralization assay, and the chemiluminescent assay can also be used for early detection and surveillance of SARS-CoV-2 infection. Finally, advancement in the next generation sequencing (NGS) and metagenomic analysis are smoothing the viral detection further in this global challenge.

Indexed as

amplificationcell-cultureCOVID-19detection-toolsdiagnosticgene-sequencingimmunoassaymicroscopySARS-CoV-2severe acute syndrome

Identifiers

PMID33762831
PMCPMC7982560
OpenAlexW3138505163

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.