Evidence map›Paper›PMID 33025503›Full record

ReviewMolecular biology reports2020

Recent advances in the nucleic acid-based diagnostic tool for coronavirus.

Pranav Kumar Prabhakar, Jyoti Lakhanpal

Open access · bronzeAbstract readReview
In one paragraph

Review in Molecular biology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.5field-weighted citation impact, top 22% 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

9 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Review
  8. SARS-CoV-2 Subgenomic N (Diagnostics (Basel, Switzerland) · 2021
    Article
  9. Antigen tests for COVID-19.Biophysics and physicobiology · 2021
    Article
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

2 authors at 1 institution in 1 country.

Pranav Kumar PrabhakarDepartment of Medical Laboratory Sciences, Lovely Professional University, Punjab, 144411, India. prabhakar.iitm@gmail.com.ORCID http://orcid.org/0000-0001-8130-1822
Jyoti LakhanpalDepartment of Medical Laboratory Sciences, Lovely Professional University, Punjab, 144411, India.
Lovely Professional University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently in China, a novel coronavirus outbreak took place which caused pneumonia-like symptoms. This coronavirus belongs to the family of SARS and MERS and causes respiratory system disease known as COVID-19. At present we use polymerase chain reaction (PCR) based molecular biology methods for the detection of coronavirus. Other than these PCR based methods, some improved methods also exist such as microarray-based techniques, Real time-quantitative PCR, CRISPR-Cas13 based tools but almost all of the available methods have advantages and disadvantages. There are many limitations associated with this method and hence there is a need for a fast, more sensitive, and specific diagnostic tool which can detect a greater number of samples in less time. Here we have summarised currently available nucleic acid-based diagnostic methods for the detection of coronavirus and the need for developing a better technique for a fast and sensitive detection of coronavirus infections. Nucleic acid based detection tool for SARS-CoV-2.

Indexed as

Molecular Diagnostic TechniquesNucleic Acid Amplification TechniquesAnimalsBetacoronavirusChinaClustered Regularly Interspaced Short Palindromic RepeatsCoronavirus InfectionsCOVID-19HumansMicroarray AnalysisPandemicsPneumonia, ViralReal-Time Polymerase Chain ReactionRNA, ViralSARS-CoV-2RNA, ViralAmplificationCoronavirusCOVID-19MicroarrayNucleic acid detectionqRT-PCR

Identifiers

PMID33025503
PMCPMC7538041
OpenAlexW3092279020

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.