Evidence map›Paper›PMID 34124407›Full record

ReviewHeliyon2021

A collection of the novel coronavirus (COVID-19) detection assays, issues, and challenges.

Erfan Rezvani Ghomi, Fatemeh Khosravi, Ali Mohseni-M, Nooshin Nourbakhsh, Mahsa Haji Mohammad Hoseini, Sunpreet Singh, Mikael S Hedenqvist, Seeram Ramakrishna

Open access · goldAbstract readReview
In one paragraph

Review in Heliyon, 2021. 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
0.7field-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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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

8 authors at 4 institutions in 5 countries.

Erfan Rezvani GhomiCenter for Nanotechnology and Sustainability, Department of Mechanical Engineering, National University of Singapore, Singapore, 117581, Singapore.
Fatemeh KhosraviCenter for Nanotechnology and Sustainability, Department of Mechanical Engineering, National University of Singapore, Singapore, 117581, Singapore.
Ali Mohseni-MExecutive Vice President and Chief Food Safety Officer, American Foods Group, LLC, 500 South Washington St., Green Bay, WI, 54301, USA.
Nooshin NourbakhshYong Loo Lin School of Medicine, Department of Medicine, National University of Singapore, Singapore, 119228, Singapore.
Mahsa Haji Mohammad HoseiniEmergency Department, Paramedical Faculty, Qom University of Medical Sciences, Qom, 3713649373, Iran.
Sunpreet SinghCenter for Nanotechnology and Sustainability, Department of Mechanical Engineering, National University of Singapore, Singapore, 117581, Singapore.
Mikael S HedenqvistDepartment of Fibre and Polymer Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, 100 44, Sweden.
Seeram RamakrishnaCenter for Nanotechnology and Sustainability, Department of Mechanical Engineering, National University of Singapore, Singapore, 117581, Singapore.
National University of Singapore · SGKTH Royal Institute of Technology · SEPhoenix (United States) · USQom University of Medical Science and Health Services · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global pandemic of COVID-19 has rapidly increased the number of infected cases as well as asymptomatic individuals in many, if not all the societies around the world. This issue increases the demand for accurate and rapid detection of SARS-CoV-2. While accurate and rapid detection is critical for diagnosing SARS-CoV-2, the appropriate course of treatment must be chosen to help patients and prevent its further spread. Testing platform accuracy with high sensitivity and specificity for SARS-CoV-2 is equally important for clinical, regional, and global arenas to mitigate secondary transmission rounds. The objective of this article is to compare the current detection technology and introduce the most accurate and rapid ones that are suitable for pandemic circumstances. Hence, the importance of rapid detection in societies is discussed initially. Following this, the current technology for rapid detection of SARS-CoV-2 is explained and classified into three different categories: nucleic acid-based, protein-based, and point of care (PoC) detection testing. Then, the current issues for diagnostic procedures in laboratories are discussed. Finally, the role of new technologies in countering COVID-19 is also introduced to assist researchers in the development of accurate and timely detection of coronaviruses. As coronavirus continues to affect human lives in a detrimental manner, the development of rapid and accurate virus detection methods could promote COVID-19 diagnosis accessible to both individuals and the mass population at patient care. In this regard, rRT-PCR and multiplex RT-PCR detection techniques hold promise.

Indexed as

COVID-19PandemicPolymerase chain reactionRapid detection techniquesSafetySARS-CoV-2Technology

Identifiers

PMID34124407
PMCPMC8179727
OpenAlexW3172179763

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.