Evidence map›Paper›PMID 32987722›Full record

ArticleDiagnostics (Basel, Switzerland)2020

A Rapid SARS-CoV-2 RT-PCR Assay for Low Resource Settings.

Arunkumar Arumugam, Matthew L Faron, Peter Yu, Cole Markham, Michelle Wu, Season Wong

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.4field-weighted citation impact, top 24% 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

10 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
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  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. High-throughput and automated screening for COVID-19.Frontiers in medical technology · 2022
    Review
  9. Article
  10. Review
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.

Arunkumar ArumugamAI Biosciences, Inc., College Station, TX 77845, USA.
Matthew L FaronThe Medical College of Wisconsin, Milwaukee, WI 53226, USA.
Peter YuAI Biosciences, Inc., College Station, TX 77845, USA.
Cole MarkhamAI Biosciences, Inc., College Station, TX 77845, USA.
Michelle WuAI Biosciences, Inc., College Station, TX 77845, USA.
Season WongAI Biosciences, Inc., College Station, TX 77845, USA.ORCID 0000-0001-5264-0286
AI Biosciences (United States) · USMedical College of Wisconsin · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay is the gold standard recommended to test for acute SARS-CoV-2 infection. However, it generally requires expensive equipment such as RNA isolation instruments and real-time PCR thermal cyclers. As a pandemic, COVID-19 has spread indiscriminately, and many low resource settings and developing countries do not have the means for fast and accurate COVID-19 detection to control the outbreak. Additionally, long assay times, in part caused by slow sample preparation steps, have created a large backlog when testing patient samples suspected of COVID-19. With many PCR-based molecular assays including an extraction step, this can take a significant amount of time and labor, especially if the extraction is performed manually. Using COVID-19 clinical specimens, we have collected evidence that the RT-qPCR assay can feasibly be performed directly on patient sample material in virus transport medium (VTM) without an RNA extraction step, while still producing sensitive test results. If RNA extraction steps can be omitted without significantly affecting clinical sensitivity, the turn-around time of COVID-19 tests, and the backlog we currently experience can be reduced drastically. Furthermore, our data suggest that rapid RT-PCR can be implemented for sensitive and specific molecular diagnosis of COVID-19 in locations where sophisticated laboratory instruments are not available. Our USD 300 set up achieved rapid RT-PCR using thin-walled PCR tubes and a water bath setup using sous vide immersion heaters, a Raspberry Pi computer, and a single servo motor that can process up to 96 samples at a time. Using COVID-19 positive clinical specimens, we demonstrated that RT-PCR assays can be performed in as little as 12 min using untreated samples, heat-inactivated samples, or extracted RNA templates with our low-cost water bath setup. These findings can help rapid COVID-19 testing to become more accessible and attainable across the globe.

Indexed as

low resource settingrapid RT-PCR assayRNASARS-CoV-2 virusthermal cycler

Identifiers

PMID32987722
PMCPMC7598596
OpenAlexW3089228730

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.