Evidence map›Paper›PMID 33649735›Full record

ArticleACS central science2021

Handheld Point-of-Care System for Rapid Detection of SARS-CoV-2 Extracted RNA in under 20 min.

Jesus Rodriguez-Manzano, Kenny Malpartida-Cardenas, Nicolas Moser, Ivana Pennisi, Matthew Cavuto, Luca Miglietta, Ahmad Moniri, Rebecca Penn, Giovanni Satta, Paul Randell and 5 more

Open access · diamondAbstract read
In one paragraph

Article in ACS central science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 4 pooled it
10.8field-weighted citation impact, top 1% 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

72 citing papers in PubMed, 4 syntheses or guidelines pooled it, 146 citations in OpenAlex.

  1. Pooled it
  2. Rapid, point-of-care antigen tests for diagnosis of SARS-CoV-2 infection.The Cochrane database of systematic reviews · 2022
    Pooled it
  3. Pooled it
  4. Nucleic acid amplification tests on respiratory samples for the diagnosis of coronavirus infections: a systematic review and meta-analysis.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2021
    Pooled it
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12 more citing papers are in PubMed but not listed here.

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

15 authors at 2 institutions in 1 country.

Jesus Rodriguez-ManzanoDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom.
Kenny Malpartida-CardenasDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom.
Nicolas MoserDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom.
Ivana PennisiDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom.
Matthew CavutoDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom.
Luca MigliettaDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom.
Ahmad MoniriDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom.
Rebecca PennDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom.
Giovanni SattaImperial College Healthcare NHS Trust, Hammersmith Hospital, London W12 0HS, United Kingdom.
Paul RandellImperial College Healthcare NHS Trust, Hammersmith Hospital, London W12 0HS, United Kingdom.
Frances DaviesDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom.
Frances BoltDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom.
Wendy BarclayDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom.
Alison HolmesDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom.
Pantelis GeorgiouDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom.
Imperial College London · GBImperial College Healthcare NHS Trust · GB

Funding

Medical Research Council MC_PC_16046Medical Research Council MR/T005254/1
6 · The paper itself

Abstract

The COVID-19 pandemic is a global health emergency characterized by the high rate of transmission and ongoing increase of cases globally. Rapid point-of-care (PoC) diagnostics to detect the causative virus, SARS-CoV-2, are urgently needed to identify and isolate patients, contain its spread and guide clinical management. In this work, we report the development of a rapid PoC diagnostic test (<20 min) based on reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) and semiconductor technology for the detection of SARS-CoV-2 from extracted RNA samples. The developed LAMP assay was tested on a real-time benchtop instrument (RT-qLAMP) showing a lower limit of detection of 10 RNA copies per reaction. It was validated against extracted RNA from 183 clinical samples including 127 positive samples (screened by the CDC RT-qPCR assay). Results showed 91% sensitivity and 100% specificity when compared to RT-qPCR and average positive detection times of 15.45 ± 4.43 min. For validating the incorporation of the RT-LAMP assay onto our PoC platform (RT-eLAMP), a subset of samples was tested (

Identifiers

PMID33649735
PMCPMC7839415
OpenAlexW3120630492

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.