Evidence map›Paper›PMID 37368738›Full record

ArticleTropical medicine and infectious disease2023

Laboratory Evaluation of a SARS-CoV-2 RT-LAMP Test.

Sandra Menting, Annette Erhart, Henk D F H Schallig

Open access · goldAbstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 48% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 2 institutions in 2 countries.

Sandra MentingAmsterdam University Medical Centres, Academic Medical Centre at the University of Amsterdam, Laboratory for Experimental Parasitology, Department of Clinical Microbiology and Infection Prevention, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.
Annette ErhartMRC Unit The Gambia at the LSHTM, Atlantic Boulevard, Fajara, Banjul P.O. Box 273, The Gambia.
Henk D F H SchalligAmsterdam University Medical Centres, Academic Medical Centre at the University of Amsterdam, Laboratory for Experimental Parasitology, Department of Clinical Microbiology and Infection Prevention, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.ORCID 0000-0002-7096-6279
University of Amsterdam · NLMRC Unit the Gambia · GM

Funding

European Developping Countries Clinical Trials Partnership RIA2020EF-3012
6 · The paper itself

Abstract

There is a need to have more accessible molecular diagnostic tests for the diagnosis of severe acute respiratory syndrome coronavirus 2 disease in low- and middle-income countries. Reverse transcription loop-mediated isothermal amplification (RT-LAMP) may provide an attractive option as this technology does not require a complex infrastructure. In this study, the diagnostic performance of a SARS-CoV-2 RT-LAMP was evaluated using RT-PCR-confirmed clinical specimens of COVID-19-positive (n = 55) and -negative patients (n = 55) from the Netherlands. The observed sensitivity of the RT-LAMP test was 97.2% (95% CI: 82.4-98.0%) and the specificity was 100% (95% CI: 93.5-100%). The positive predictive value of the RT-LAMP was 100%, the negative predictive value 93.2% (95% CI: 84.3-97.3%), and the diagnostic accuracy was 96.4% (95% CI: 91.0-99.0%). The agreement between the RT-LAMP and the RT-PCR was "almost perfect" (κ-value: 0.92). The evaluated RT-LAMP might provide an attractive alternative molecular diagnostic tool for SARS-CoV-2 in resource limited settings.

Indexed as

COVID-19LMICsmolecular diagnosticperformanceRT-LAMPRT-PCR

Identifiers

PMID37368738
PMCPMC10302189
OpenAlexW4380686343

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.