Evidence map›Paper›PMID 35155505›Full record

ArticleFrontiers in medicine2022

Demographic, Virological Characteristics and Prognosis of Asymptomatic COVID-19 Patients in South China.

Hui Xu, Cheng-Yuan Xie, Pei-Hong Li, Zhong-Liang Ji, Jiu-Feng Sun, Bei Hu, Xin Li, Ming Fang

Abstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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.

Hui XuGuangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Cheng-Yuan XieGuangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Pei-Hong LiGuangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Zhong-Liang JiGuangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Jiu-Feng SunGuangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
Bei HuGuangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Xin LiGuangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Ming FangGuangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAsymptomatic transmission is a major concern for SARS-CoV-2 community spread; however, little information is available on demographic, virological characteristics and prognosis of asymptomatic cases.

methodsAll COVID-19 patients hospitalized in Guangdong Province from September 1, 2020 to February 28, 2021, were included and were divided into asymptomatic and symptomaticgroup. The source country of all patients, clinical laboratory test results, the genotype of virus and the time of SARS-CoV-2 RNA turning negative or hospitalization were confirmed.

resultsTotal 233 patients from 57 different countries or regions were included, with 83 (35.6%) asymptomatic and 150 (64.4%) symptomatic patients. Asymptomatic cases were younger (

conclusionsThe asymptomatic cases are prone to develop in patients with younger age, less comorbidities andinfected with B.1.1 and B.1.524 variants. More attention should be paid for lineage B.1.524 because it can significantly prolong the SARS-CoV-2 RNA negative conversion time and hospitalization in infected cases.

Indexed as

asymptomatic patientsCOVID-19epidemiologyprognosisvariants

Identifiers

PMID35155505
PMCPMC8831799

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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.