Evidence map›Paper›PMID 32402515›Full record

SynthesisCurrent problems in cardiology2020

Association of Cardiovascular Disease With Coronavirus Disease 2019 (COVID-19) Severity: A Meta-Analysis.

Gaurav Aggarwal, Isaac Cheruiyot, Saurabh Aggarwal, Johnny Wong, Giuseppe Lippi, Carl J Lavie, Brandon M Henry, Fabian Sanchis-Gomar

Open access · greenAbstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Current problems in cardiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed, 12 pooled it
4.1field-weighted citation impact, top 4% 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

99 citing papers in PubMed, 12 syntheses or guidelines pooled it, 201 citations in OpenAlex.

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  10. Clinical Characteristics of Stroke with COVID-19: A Systematic Review and Meta-Analysis.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2020
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39 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

8 authors.

Gaurav Aggarwal
Isaac Cheruiyot
Saurabh Aggarwal
Johnny Wong
Giuseppe Lippi
Carl J Lavie
Brandon M Henry
Fabian Sanchis-Gomar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Observational studies have reported an association between underlying cardiovascular diseases (CVD) and worse prognosis in COVID-19 patients, but this still remains unclear. We conducted a meta-analysis of recent studies that reported the association of CVD with worse prognosis and increased mortality in COVID-19 patients. Literature search through PubMed, the Cochrane Library, and Embase was completed by 2 reviewers from November 1, 2019 to April 20, 2020. Inclusion criteria were observational case-control or cohort studies on COVID-19 patients with a history of CVD included, which reported outcomes of COVID-19 infection severity, clearly outlined the definition of "severe disease" and with sample size >10. Data were abstracted independently by 2 authors. Studies were divided into 2 separate cohorts for analysis: severity (severe vs nonsevere) and mortality (nonsurvivors vs survivors). Data was pooled into a meta-analysis to estimate pooled odds ratio (OR) with 95% confidence interval (95% CI) for each outcome. A total of 18 studies (n = 4858 patients) were included. Sixteen studies were from China, while 2 were from the United States. Pre-existing CVD was associated with a significantly increased risk of a severe form of COVID-19 (OR = 3.14; 95% CI 2.32-4.24; I

Indexed as

Cardiovascular DiseasesCoronavirus InfectionsMortalityPandemicsPneumonia, ViralSeverity of Illness IndexBetacoronavirusComorbidityCOVID-19HumansObservational Studies as TopicPrognosisRisk AssessmentSARS-CoV-2

Identifiers

PMID32402515
PMCPMC7187816
OpenAlexW3020561553

What OpenQuestion holds

Textmetadata
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.