Evidence map›Paper›PMID 31575036›Full record

ReviewSensors (Basel, Switzerland)2019

Developments in the HCV Screening Technologies Based on the Detection of Antigens and Antibodies.

Shrikant Dashrath Warkad, Keum-Soo Song, Dilipkumar Pal, Satish Balasaheb Nimse

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–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

16 citing papers in PubMed.

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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.

Shrikant Dashrath WarkadInstitute of Applied Chemistry and Department of Chemistry, Hallym University, Chuncheon 200-702, Korea. shrikant.warkad@hallym.ac.kr.
Keum-Soo SongInstitute of Applied Chemistry and Department of Chemistry, Hallym University, Chuncheon 200-702, Korea. hanlimsk@empal.com.
Dilipkumar PalInstitute of Pharmaceutical Sciences, Guru Ghasidas Vishwavidyalaya (A Central University), Koni 495009, Bilaspur, India. drdilip71@gmail.com.
Satish Balasaheb NimseInstitute of Applied Chemistry and Department of Chemistry, Hallym University, Chuncheon 200-702, Korea. satish_nimse@hallym.ac.kr.

Funding

Hallym University HRF-201901-006Leaders in Industry-university Cooperation+ (LINC+) Project, supported by the Ministry of Education (MOE) H20190748
6 · The paper itself

Abstract

Hepatitis C virus (HCV) accounts for 15%-20% of cases of acute infection, and chronic HCV infection is developed in about 50%-80% of HCV patients. Unfortunately, due to the lack of proper medical care, difficulty in screening for HCV infection, and lack of awareness resulted in chronic HCV infection in 71 million people on a global scale, and about 399,000 deaths in 2016. It is crucial to recognize that the effective use of antiviral medicines can cure more than 95% of HCV infected people. The Global Health Sector Strategy (GHSS) aim is to reduce the new HCV infections and the HCV associated mortality by 90% and 65%, respectively. Therefore, the methods that are simple, yet powerful enough to detect HCV infections with high sensitivity, specificity, and a shorter window period are crucial to restrain the global burden of HCV healthcare. This article focuses on the technologies used for the detection of HCV in clinical specimens.

Indexed as

Antibodies, ViralAntigens, ViralElectrochemical TechniquesHepacivirusHepatitis CHumansImmunoblottingImmunoenzyme TechniquesLuminescenceViral ProteinsAntibodies, ViralAntigens, ViralViral Proteinsanti-HCV antibodyFlaviviridaeHCV core antigenHCV detectionNS3NS4NS5viruses

Identifiers

PMID31575036
PMCPMC6806196

What OpenQuestion holds

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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.