Evidence map›Paper›PMID 34930933›Full record

ArticleScientific reports2021

Evaluation of reverse transcription-loop-mediated isothermal amplification for rapid detection of SARS-CoV-2.

Willi Quino, Diana Flores-León, Junior Caro-Castro, Carmen V Hurtado, Iris Silva, Ronnie G Gavilan

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

6 authors at 2 institutions in 1 country.

Willi QuinoInstituto Nacional de Salud, Lima, Perú.
Diana Flores-LeónInstituto Nacional de Salud, Lima, Perú.
Junior Caro-CastroInstituto Nacional de Salud, Lima, Perú.
Carmen V HurtadoInstituto Nacional de Salud, Lima, Perú.
Iris SilvaInstituto Nacional de Salud, Lima, Perú.
Ronnie G GavilanInstituto Nacional de Salud, Lima, Perú. rgavilan@ins.gob.pe.
Instituto Nacional de Salud · PEUniversidad Privada San Juan Bautista · PE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The main strategy for response and control of COVID-19 demands the use of rapid, accurate diagnostic tests aimed at the first point of health care. During the emergency, an increase in asymptomatic and symptomatic cases results in a great demand for molecular tests, which is promoting the development and application of rapid diagnostic technologies. In this study, we describe the development and evaluation of RT-LAMP to detect SARS-CoV-2 based on three genes (ORF1ab, M and N genes) in monoplex and triplex format. RT-LAMP assays were compared with the gold standard method RT-qPCR. The triplex format (RdRp, M and N genes) allowed obtaining comparable results with de RT-qPCR (RdRp and E genes), presented a sensitivity of 98.9% and a specificity of 97.9%, opening the opportunity to apply this method to detect SARS-CoV-2 at primary health-care centers.

Indexed as

Coronavirus M ProteinsCoronavirus RNA-Dependent RNA PolymeraseCOVID-19COVID-19 Nucleic Acid TestingHumansLimit of DetectionMolecular Diagnostic TechniquesNasopharynxNucleic Acid Amplification TechniquesNucleocapsid ProteinsPoint-of-Care SystemsRNA, ViralSARS-CoV-2Viral Matrix ProteinsCoronavirus M ProteinsCoronavirus RNA-Dependent RNA Polymerasemembrane protein, SARS-CoV-2NSP12 protein, SARS-CoV-2Nucleocapsid ProteinsRNA, ViralViral Matrix Proteins

Identifiers

PMID34930933
PMCPMC8688429
OpenAlexW4200328962

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.