Evidence map›Paper›PMID 32466458›Full record

ReviewViruses2020

Challenges in Laboratory Diagnosis of the Novel Coronavirus SARS-CoV-2.

Nadin Younes, Duaa W Al-Sadeq, Hadeel Al-Jighefee, Salma Younes, Ola Al-Jamal, Hanin I Daas, Hadi M Yassine, Gheyath K Nasrallah

Open access · goldAbstract readReview
In one paragraph

Review in Viruses, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 207 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
207citing papers in PubMed, 6 pooled it
9.7field-weighted citation impact, top 2% 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

207 citing papers in PubMed, 6 syntheses or guidelines pooled it, 428 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Recent advances in the diagnosis of COVID-19: a bird's eye view.Expert review of molecular diagnostics · 2021
    Pooled it
  5. Kawasaki-like disease in children with COVID-19.Rheumatology international · 2020
    Pooled it
  6. The incidence of the novel coronavirus SARS-CoV-2 among asymptomatic patients: A systematic review.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020
    Pooled it
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Proteomic Analysis of COVID-19 Infection.Advances in experimental medicine and biology · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

147 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

8 authors at 1 institution in 1 country.

Nadin YounesBiomedical Research Center, Qatar University, P.O. Box 2713 Doha, Qatar.
Duaa W Al-SadeqBiomedical Research Center, Qatar University, P.O. Box 2713 Doha, Qatar.
Hadeel Al-JighefeeBiomedical Research Center, Qatar University, P.O. Box 2713 Doha, Qatar.
Salma YounesDepartment of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University P.O. Box 2713 Doha, Qatar.
Ola Al-JamalBiomedical Research Center, Qatar University, P.O. Box 2713 Doha, Qatar.
Hanin I DaasCollege of Dental Medicine, Member of QU Health, Qatar University, P.O. Box 2713 Doha, Qatar.
Hadi M YassineBiomedical Research Center, Qatar University, P.O. Box 2713 Doha, Qatar.
Gheyath K NasrallahBiomedical Research Center, Qatar University, P.O. Box 2713 Doha, Qatar.
Qatar University · QA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent outbreak of the Coronavirus disease 2019 (COVID-19) has quickly spread worldwide since its discovery in Wuhan city, China in December 2019. A comprehensive strategy, including surveillance, diagnostics, research, clinical treatment, and development of vaccines, is urgently needed to win the battle against COVID-19. The past three unprecedented outbreaks of emerging human coronavirus infections at the beginning of the 21st century have highlighted the importance of readily available, accurate, and rapid diagnostic technologies to contain emerging and re-emerging pandemics. Real-time reverse transcriptase-polymerase chain reaction (rRT-PCR) based assays performed on respiratory specimens remain the gold standard for COVID-19 diagnostics. However, point-of-care technologies and serologic immunoassays are rapidly emerging with high sensitivity and specificity as well. Even though excellent techniques are available for the diagnosis of symptomatic patients with COVID-19 in well-equipped laboratories; critical gaps still remain in screening asymptomatic people who are in the incubation phase of the virus, as well as in the accurate determination of live viral shedding during convalescence to inform decisions for ending isolation. This review article aims to discuss the currently available laboratory methods and surveillance technologies available for the detection of COVID-19, their performance characteristics and highlight the gaps in current diagnostic capacity, and finally, propose potential solutions. We also summarize the specifications of the majority of the available commercial kits (PCR, EIA, and POC) for laboratory diagnosis of COVID-19.

Indexed as

Clinical Laboratory TechniquesAsymptomatic InfectionsBetacoronavirusCoronavirus InfectionsCOVID-19COVID-19 TestingCOVID-19 VaccinesHumansImmunoenzyme TechniquesNeutralization TestsNucleic Acid Amplification TechniquesPandemicsPneumonia, ViralPoint-of-Care TestingReagent Kits, DiagnosticReal-Time Polymerase Chain ReactionCovid-19 aAPC vaccineCOVID-19 VaccinesReagent Kits, DiagnosticCOVID-19diagnostic challengesmolecular testingSARS-CoV-2serologyviruses

Identifiers

PMID32466458
PMCPMC7354519
OpenAlexW3032292222

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.