Evidence map›Paper›PMID 33344540›Full record

ReviewWorld journal of clinical cases2020

COVID-19: A review of what radiologists need to know.

Lei Tang, Yi Wang, Yun Zhang, Xiao-Yong Zhang, Xian-Chun Zeng, Bin Song

Open access · diamondAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in World journal of clinical cases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 47% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. A comprehensive review of imaging findings in COVID-19 - status in early 2021.European journal of nuclear medicine and molecular imaging · 2021
    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

6 authors at 2 institutions in 1 country.

Lei TangDepartment of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
Yi WangDepartment of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
Yun ZhangDepartment of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
Xiao-Yong ZhangDepartment of Radiology, Guizhou Provincial People's Hospital, Key Laboratory of Intelligent Medical Imaging Analysis and Accurate Diagnosis of Guizhou Province, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guiyang 550002, Guizhou Province, China.
Xian-Chun ZengDepartment of Radiology, Guizhou Provincial People's Hospital, Key Laboratory of Intelligent Medical Imaging Analysis and Accurate Diagnosis of Guizhou Province, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guiyang 550002, Guizhou Province, China.
Bin SongDepartment of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China. songlab_radiology@163.com.
Sichuan University · CNWest China Hospital of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease-2019 (COVID-19) is spreading throughout the world. Chest radiography and computed tomography play an important role in disease diagnosis, differential diagnosis, severity evaluation, prognosis prediction, therapeutic effects assessment and follow-up of patients with COVID-19. In this review, we summarize knowledge of COVID-19 pneumonia that may help improve the abilities of radiologists to diagnose and evaluate this highly infectious disease, which is essential for epidemic control and preventing new outbreaks in the short term.

Indexed as

Coronavirus infectionDiagnosisLungPneumoniaRadiology

Identifiers

PMID33344540
PMCPMC7716304
OpenAlexW3108775334

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.