Evidence map›Paper›PMID 34423408›Full record

ReviewApplied microbiology and biotechnology2021

Cross-disciplinary approaches to assist with nucleic acid testing for SARS-CoV-2.

Shujuan Yang, Xiongfeng Pan, Dan Yuan, Peibin Zeng, Peng Jia

Open access · bronzeAbstract readReview
In one paragraph

Review in Applied microbiology and biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
0.3field-weighted citation impact, top 39% 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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Auxiliary Screening COVID-19 by Serology.Frontiers in public health · 2022
    Pooled it
  3. Review
  4. Article
  5. 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

5 authors at 4 institutions in 1 country.

Shujuan Yang *West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Xiongfeng Pan *International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China.
Dan YuanSichuan Center for Disease Control and Prevention, Chengdu, China.
Peibin ZengWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China. zengpeibin@live.cn.
Peng JiaInternational Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China. jiapengff@hotmail.com.ORCID http://orcid.org/0000-0003-0110-3637
Sichuan University · CNCentral South University · CNSichuan Center for Disease Control and Prevention · CNWuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improving the capacity of detecting positive severe acute respiratory syndrome coronavirus 2 is critical for identifying the infection of coronavirus disease 2019 (COVID-19) precisely and thereby curbing the pandemic. Cross-disciplinary approaches may improve the efficiency of COVID-19 diagnosis by compensating to some extent the limitations encountered by traditional test methods during the COVID-19 pandemic. Combining computed tomography (CT), serum-specific antibody detection, and nanopore sequencing with nucleic acid testing for individual testing may improve the accuracy of identifying COVID-19 patients. At community or even regional/national levels, the combination of pooled screening and spatial epidemiological strategies may enable the detection of early transmission of epidemics in a cost-effective way, which is also less affected by restricted access to diagnostic tests and kit supplies. This would significantly advance our capacity of curbing epidemics as soon as possible, and better prepare us for entering a new era of high-impact and high-frequency epidemics.

Indexed as

COVID-19Nucleic AcidsCOVID-19 TestingHumansPandemicsSARS-CoV-2Nucleic AcidsCOVID-19CTNucleic acid testingSamplingSARS-CoV-2Spatial epidemiology

Identifiers

PMID34423408
PMCPMC8380513
OpenAlexW3194589000

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.