Evidence map›Paper›PMID 34201849›Full record

ReviewBiosensors2021

Dengue Detection: Advances in Diagnostic Tools from Conventional Technology to Point of Care.

Md Alamgir Kabir, Hussein Zilouchian, Muhammad Awais Younas, Waseem Asghar

Abstract readReview
In one paragraph

Review in Biosensors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

48 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Md Alamgir KabirAsghar-Lab, Micro and Nanotechnology in Medicine, College of Engineering and Computer Science, Boca Raton, FL 33431, USA.ORCID 0000-0002-1659-3125
Hussein ZilouchianAsghar-Lab, Micro and Nanotechnology in Medicine, College of Engineering and Computer Science, Boca Raton, FL 33431, USA.
Muhammad Awais YounasServices Institute of Medical Sciences, Lahore 54000, Pakistan.ORCID 0000-0003-4306-0831
Waseem AsgharAsghar-Lab, Micro and Nanotechnology in Medicine, College of Engineering and Computer Science, Boca Raton, FL 33431, USA.ORCID 0000-0003-0458-8430

Funding

National Science Foundation CAREER 1942487National Science Foundation RAPID 2027890
6 · The paper itself

Abstract

The dengue virus (DENV) is a vector-borne flavivirus that infects around 390 million individuals each year with 2.5 billion being in danger. Having access to testing is paramount in preventing future infections and receiving adequate treatment. Currently, there are numerous conventional methods for DENV testing, such as NS1 based antigen testing, IgM/IgG antibody testing, and Polymerase Chain Reaction (PCR). In addition, novel methods are emerging that can cut both cost and time. Such methods can be effective in rural and low-income areas throughout the world. In this paper, we discuss the structural evolution of the virus followed by a comprehensive review of current dengue detection strategies and methods that are being developed or commercialized. We also discuss the state of art biosensing technologies, evaluated their performance and outline strategies to address challenges posed by the disease. Further, we outline future guidelines for the improved usage of diagnostic tools during recurrence or future outbreaks of DENV.

Indexed as

Point-of-Care SystemsAntibodies, ViralDengueEnzyme-Linked Immunosorbent AssayHumansImmunoglobulin GSensitivity and SpecificityAntibodies, ViralImmunoglobulin Gdenguediagnosticspoint-of-care

Identifiers

PMID34201849
PMCPMC8301808

What Socratic 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 Socratic graph.