Evidence mapPaperPMID 33939733Full record

SynthesisPloS one2021

Clinical determinants of the severity of COVID-19: A systematic review and meta-analysis.

Xinyang Li, Xianrui Zhong, Yongbo Wang, Xiantao Zeng, Ting Luo, Qing Liu

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
112citing papers in PubMed, 6 pooled it
15.1field-weighted citation impact, top 1% 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

112 citing papers in PubMed, 6 syntheses or guidelines pooled it, 251 citations in OpenAlex.

  1. Pooled it
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  5. COVID-19 Prevalence among Healthcare Workers. A Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2021
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  18. From test to rest: evaluating socioeconomic differences along the COVID-19 care pathway in the Netherlands.The European journal of health economics : HEPAC : health economics in prevention and care · 2024
    Observational
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52 more citing papers are in PubMed but not listed here.

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 2 countries.

Xinyang LiSchool of Stomatology, Wuhan University, Wuhan, Hubei, China.ORCID 0000-0003-3010-5586
Xianrui ZhongDepartment of Computer Science, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America.
Yongbo WangCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.
Xiantao ZengCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.
Ting LuoSchool of Stomatology, Wuhan University, Wuhan, Hubei, China.
Qing LiuDepartment of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, Hubei, China.ORCID 0000-0003-2028-973X
Wuhan University · CNUniversity of Illinois Urbana-Champaign · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe aimed to systematically identify the possible risk factors responsible for severe cases.

methodsWe searched PubMed, Embase, Web of science and Cochrane Library for epidemiological studies of confirmed COVID-19, which include information about clinical characteristics and severity of patients' disease. We analyzed the potential associations between clinical characteristics and severe cases.

resultsWe identified a total of 41 eligible studies including 21060 patients with COVID-19. Severe cases were potentially associated with advanced age (Standard Mean Difference (SMD) = 1.73, 95% CI: 1.34-2.12), male gender (Odds Ratio (OR) = 1.51, 95% CI:1.33-1.71), obesity (OR = 1.89, 95% CI: 1.44-2.46), history of smoking (OR = 1.40, 95% CI:1.06-1.85), hypertension (OR = 2.42, 95% CI: 2.03-2.88), diabetes (OR = 2.40, 95% CI: 1.98-2.91), coronary heart disease (OR: 2.87, 95% CI: 2.22-3.71), chronic kidney disease (CKD) (OR = 2.97, 95% CI: 1.63-5.41), cerebrovascular disease (OR = 2.47, 95% CI: 1.54-3.97), chronic obstructive pulmonary disease (COPD) (OR = 2.88, 95% CI: 1.89-4.38), malignancy (OR = 2.60, 95% CI: 2.00-3.40), and chronic liver disease (OR = 1.51, 95% CI: 1.06-2.17). Acute respiratory distress syndrome (ARDS) (OR = 39.59, 95% CI: 19.99-78.41), shock (OR = 21.50, 95% CI: 10.49-44.06) and acute kidney injury (AKI) (OR = 8.84, 95% CI: 4.34-18.00) were most likely to prevent recovery. In summary, patients with severe conditions had a higher rate of comorbidities and complications than patients with non-severe conditions.

conclusionPatients who were male, with advanced age, obesity, a history of smoking, hypertension, diabetes, malignancy, coronary heart disease, hypertension, chronic liver disease, COPD, or CKD are more likely to develop severe COVID-19 symptoms. ARDS, shock and AKI were thought to be the main hinderances to recovery.

Indexed as

ComorbidityAdultAgedAged, 80 and overAge FactorsCerebrovascular DisordersCOVID-19Diabetes MellitusFemaleHumansHypertensionLiver DiseasesMaleMiddle AgedNeoplasmsObesity

Identifiers

PMID33939733
PMCPMC8092779
OpenAlexW3159647759

What Socratic 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 Socratic graph.