Evidence map›Paper›PMID 32805730›Full record

ArticleAging2020

Risk factors for severe cases of COVID-19: a retrospective cohort study.

Feng He, Qingqing Luo, Ming Lei, Lixin Fan, Xinning Shao, Guanglie Huang, Jun Zeng, Ziwen Zhao, Shuguang Qin, Zhi Yang and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
0.6field-weighted citation impact, top 19% 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.

  1. Pooled it
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  11. Euthyroid Sick Syndrome in Patients With COVID-19.Frontiers in endocrinology · 2020
    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

13 authors at 4 institutions in 1 country.

Feng HeGuangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Qingqing LuoGuangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Ming LeiGuangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
Lixin FanGuangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
Xinning ShaoGuangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
Guanglie HuangGuangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Jun ZengGuangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Ziwen ZhaoGuangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Shuguang QinGuangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Zhi YangGuangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Na YuGuangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Liuping YangGuangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
Jie CaoGuangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, China.
Guangzhou Medical University · CNSouth China University of Technology · CNGuangzhou Eighth People's Hospital · CNGuangzhou First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSARS-CoV-2 has raged around the world since March, 2020. We aim to describe the clinical characteristics and risk factors of severe patients with COVID-19 in Guangzhou.

resultsThe severity and mortality of COVID-19 was 10.4% and 0.3% respectively. And each 1-year increase in age (OR, 1.057; 95% CI, 1.018-1.098; P=0.004), Wuhan exposure history greater than 2 weeks (OR, 2.765; 95% CI, 1.040-7.355; P=0.042), diarrhea (OR, 24.349; 95% CI, 3.580-165.609; P=0.001), chronic kidney disease (OR, 6.966; 95% CI, 1.310-37.058; P = 0.023), myoglobin higher than 106 μg/L (OR, 8.910; 95% CI, 1.225-64.816; P=0.031), white blood cell higher than 10×10

conclusionOlder age, Wuhan exposure history, diarrhea, chronic kidney disease, elevated myoglobin, elevated white blood cell and C-reactive protein were independent risk factors for severe patients with COVID-19 in Guangzhou.

methodsWe included 288 adult patients with COVID-19 and compared the data between severe and non-severe group. We used univariate and multivariate logistic regression methods to explore risk factors of severe cases.

Indexed as

Coronavirus InfectionsDiarrheaPandemicsPneumonia, ViralAge FactorsBetacoronavirusChinaCOVID-19C-Reactive ProteinFemaleHumansInfectious Disease Incubation PeriodLeukocyte CountMaleMiddle AgedMyoglobinC-Reactive ProteinMyoglobinclinical characteristicsCOVID-19risk factorssevere cases

Identifiers

PMID32805730
PMCPMC7467392
OpenAlexW3049069222

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.