Evidence map›Paper›PMID 36712915›Full record

ArticleHeliyon2023

Evaluation of an automated CRISPR-based diagnostic tool for rapid detection of COVID-19.

Jun Xu, Yuanyuan Ma, Zhigang Song, Wei Sun, Yi Liu, Chang Shu, Hua Hua, Ming Yang, Qi Liang

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

9 authors.

Jun XuDepartment for Viral Disease Control and Prevention, Heilongjiang Provincial Center for Disease Control and Prevention, Harbin 150030, China.
Yuanyuan MaDepartment of Drug Clinical Trial, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China.
Zhigang SongPathogen Detection and Biosafety Department, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China.
Wei SunDepartment for Viral Disease Control and Prevention, Heilongjiang Provincial Center for Disease Control and Prevention, Harbin 150030, China.
Yi LiuPathogen Detection and Biosafety Department, Shanghai Public Health Clinical Center, Fudan University, Shanghai 201508, China.
Chang ShuDepartment for Viral Disease Control and Prevention, Heilongjiang Provincial Center for Disease Control and Prevention, Harbin 150030, China.
Hua HuaDepartment for Viral Disease Control and Prevention, Heilongjiang Provincial Center for Disease Control and Prevention, Harbin 150030, China.
Ming YangDepartment for Viral Disease Control and Prevention, Heilongjiang Provincial Center for Disease Control and Prevention, Harbin 150030, China.
Qi LiangDepartment for Viral Disease Control and Prevention, Heilongjiang Provincial Center for Disease Control and Prevention, Harbin 150030, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The performance of an automated commercial CRISPR/Cas based technology was evaluated and compared with routine RT-PCR testing to diagnose COVID-19. Suspected and discharged COVID-19 cases were included and tested with CRISPR-based SARS-CoV-2 test and RT-PCR assay using throat swab and sputum specimens. The diagnostic yield was calculated and compared using the McNemar test. A total of 437 patients were included for analysis, including COVID-19 (n = 171), discharged cases (n = 155), and others (n = 111). For the diagnosis of COVID-19, the CRISPR-SARS-CoV-2 test had a sensitivity and specificity of 98.2% (168/171) and 100.0% (266/266), respectively; the RT-PCR test had a sensitivity and specificity of 100.0% (171/171) and 100.0% (266/266), respectively. No significant difference was found in the sensitivity of CRISPR-SARS-CoV-2 and RT-PCR. In conclusion, the CRISPR-SARS-CoV-2 test had a comparable performance with RT-PCR and showed several advantages, such as short assay time, low cost, and no requirement for expensive equipment.

Indexed as

CRISPRDiagnosisRT-PCR

Identifiers

PMID36712915
PMCPMC9868009

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.