Evidence map›Paper›PMID 33081710›Full record

ArticleBMC infectious diseases2020

Detecting SARS-CoV-2 at point of care: preliminary data comparing loop-mediated isothermal amplification (LAMP) to polymerase chain reaction (PCR).

Marc F Österdahl, Karla A Lee, Mary Ni Lochlainn, Stuart Wilson, Sam Douthwaite, Rachel Horsfall, Alyce Sheedy, Simon D Goldenberg, Christopher J Stanley, Tim D Spector and 1 more

Abstract readComparative Study
In one paragraph

Article in BMC infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 6 pooled it
–field-weighted citation impact
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

46 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  3. 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
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  5. Universal screening for SARS-CoV-2 infection: a rapid review.The Cochrane database of systematic reviews · 2020
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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

11 authors.

Marc F ÖsterdahlDepartment of Ageing & Health, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Karla A LeeDepartment of Twin Research and Genetic Epidemiology, Kings College London, Westminster Bridge Road, London, SE1 7EH, UK.
Mary Ni LochlainnDepartment of Ageing & Health, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Stuart WilsonMicrosensDx Ltd, 2 Royal College Street, London, UK.
Sam DouthwaiteDepartment of Infection, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Rachel HorsfallDepartment of Twin Research and Genetic Epidemiology, Kings College London, Westminster Bridge Road, London, SE1 7EH, UK.
Alyce SheedyDepartment of Twin Research and Genetic Epidemiology, Kings College London, Westminster Bridge Road, London, SE1 7EH, UK.
Simon D GoldenbergDepartment of Infection, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Christopher J StanleyMicrosensDx Ltd, 2 Royal College Street, London, UK.
Tim D SpectorDepartment of Twin Research and Genetic Epidemiology, Kings College London, Westminster Bridge Road, London, SE1 7EH, UK.
Claire J StevesDepartment of Ageing & Health, Guy's and St Thomas' NHS Foundation Trust, London, UK. claire.j.steves@kcl.ac.uk.ORCID http://orcid.org/0000-0002-4910-0489

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA cost effective and efficient diagnostic tool for COVID-19 as near to the point of care (PoC) as possible would be a game changer in the current pandemic. We tested reverse transcription loop mediated isothermal amplification (RT-LAMP), a method which can produce results in under 30 min, alongside standard methods in a real-life clinical setting.

methodsThis prospective service improvement project piloted an RT-LAMP method on nasal and pharyngeal swabs on 21 residents of a high dependency care home, with two index COVID-19 cases, and compared it to multiplex tandem reverse transcription polymerase chain reaction (RT-PCR). We recorded vital signs of patients to correlate clinical and laboratory information and calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of a single swab using RT-LAMP compared with the current standard, RT-PCR, as per Standards for Reporting Diagnostic Accuracy Studies (STARD) guidelines.

resultsThe novel method accurately detected 8/10 RT-PCR positive cases and identified a further 3 positive cases. Eight further cases were negative using both methods. Using repeated RT-PCR as a "gold standard", the sensitivity and specificity of a single novel test were 80 and 73% respectively. PPV was 73% and NPV was 83%. Incorporating retesting of low signal RT-LAMP positives improved the specificity to 100%. We also speculate that hypothermia may be a significant early clinical sign of COVID-19.

conclusionsRT-LAMP testing for SARS-CoV-2 was found to be promising, fast and to work equivalently to RT-PCR methods. RT-LAMP has the potential to transform COVID-19 detection, bringing rapid and accurate testing to the PoC. RT-LAMP could be deployed in mobile community testing units, care homes and hospitals to detect disease early and prevent spread.

Indexed as

Clinical Laboratory TechniquesPoint-of-Care SystemsPreliminary DataAgedAged, 80 and overBetacoronavirusCoronavirus InfectionsCOVID-19COVID-19 TestingData AccuracyFemaleHumansMaleMiddle AgedMolecular Diagnostic TechniquesNucleic Acid Amplification Techniques

Identifiers

PMID33081710
PMCPMC7574392

What OpenQuestion holds

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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.