Evidence map›Paper›PMID 34859002›Full record

ArticleFrontiers in medicine2021

Comparison of Clinical Characteristics for Distinguishing COVID-19 From Influenza During the Early Stages in Guangdong, China.

Yongzhi Li, Huan He, Yuhan Gao, Zejin Ou, Wenqiao He, Caiyun Chen, Jiaqi Fu, Husheng Xiong, Qing Chen

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in medicine, 2021. 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
0.2field-weighted citation impact, top 45% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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 at 1 institution in 1 country.

Yongzhi LiGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Huan HeGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Yuhan GaoGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Zejin OuGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Wenqiao HeGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Caiyun ChenGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Jiaqi FuGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Husheng XiongGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Qing ChenGuangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Southern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

clinical characteristicsCOVID-19influenzaretrospective cohort studyROC curve

Identifiers

PMID34859002
PMCPMC8631935
OpenAlexW3214631562

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.