Evidence map›Paper›PMID 37974932›Full record

ArticleIEEE sensors journal2021

Potential Microfluidic Devices for COVID-19 Antibody Detection at Point-of-Care (POC): A Review.

Muhammad Tayyab, Muhammad Ahsan Sami, Hassan Raji, Srinivas Mushnoori, Mehdi Javanmard

Open access · greenAbstract read
In one paragraph

Article in IEEE sensors journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.4field-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

15 citing papers in PubMed, 52 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Muhammad TayyabDepartment of Electrical and Computer EngineeringRutgers University Piscataway NJ 08854 USA.ORCID https://orcid.org/0000-0002-4372-504X
Muhammad Ahsan SamiDepartment of Electrical and Computer EngineeringRutgers University Piscataway NJ 08854 USA.ORCID https://orcid.org/0000-0003-4064-7709
Hassan RajiDepartment of Electrical and Computer EngineeringRutgers University Piscataway NJ 08854 USA.
Srinivas MushnooriDepartment of Chemical and Biochemical EngineeringRutgers University Piscataway NJ 08854 USA.ORCID https://orcid.org/0000-0003-3275-8353
Mehdi JavanmardDepartment of Electrical and Computer EngineeringRutgers University Piscataway NJ 08854 USA.ORCID https://orcid.org/0000-0002-6297-392X
Rutgers, The State University of New Jersey · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 has been declared a global pandemic which has brought the world economy and the society to a standstill. The current emphasis of testing is on detection of genetic material of SARS-CoV-2. Such tests are useful for assessing the current state of a subject: Infected or not infected. In addition to such tests, antibody testing is necessary to stratify the population into three groups: never exposed, infected, and immune. Such a stratification is necessary for safely reopening the society and remobilizing the economy. The aim of this review article is to inform the audience of the current diagnostic and surveillance technologies that are being employed for the detection of SARS-CoV-2 antibodies along with their shortcomings, and to highlight microfluidic sensors and devices that show promise of being commercialized for detection and quantification of SARS-CoV-2 antibodies in low-resource and Point-of-Care (POC) settings.

Indexed as

Antibodybiosensorschemical and biological sensorsenzyme linked immunosorbent assay (ELISA)protein

Identifiers

PMID37974932
PMCPMC8768978
OpenAlexW3095169007

What OpenQuestion holds

Textmetadata
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.