Evidence map›Paper›PMID 32578683›Full record

SynthesisRevista do Instituto de Medicina Tropical de Sao Paulo2020

Prevalence of comorbidities in patients and mortality cases affected by SARS-CoV2: a systematic review and meta-analysis.

Omar Ariel Espinosa, Andernice Dos Santos Zanetti, Ednardo Fornanciari Antunes, Fabiana Gulin Longhi, Tatiane Amorim de Matos, Paula Franciene Battaglini

Registry-linked trialAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Revista do Instituto de Medicina Tropical de Sao Paulo, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05897528 (Impaired Insulin Regulation Determining Severity of Severe Acute Respiratory Syndrome COVID-19 Infection Confounded by Ethnicity), which is not on this map. Cited by 60 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 6 pooled it
–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.

NCT05897528 completednot on this mapstarted 2021, after this paper: background citation

Impaired Insulin Regulation Determining Severity of Severe Acute Respiratory Syndrome COVID-19 Infection Confounded by Ethnicity

TypeobservationalSponsorArrowhead Regional Medical CenterRan2021 to 2022Enrolled589ConditionsCOVID-19, Diabetes Mellitus, COVID-19 Pneumonia, COVID-19 Respiratory InfectionArmsNo Intervention
3 · Its place in the literature

Who cites it

60 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  6. Is there any potential management against COVID-19? A systematic review and meta-analysis.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2020
    Pooled it
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  9. Altitude and case fatality rate from COVID-19 during the pandemic in Peru, 2020-2022.Revista peruana de medicina experimental y salud publica · 2026
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  11. COVID-19 case fatality ratio and survival among hospitalized adults in Goiás, 2020: a cohort study.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2025
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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

6 authors.

Omar Ariel EspinosaFaculdade do Pantanal, Cáceres, Mato Grosso, Brazil.ORCID http://orcid.org/0000-0002-0912-9527
Andernice Dos Santos ZanettiUniversidade do Estado de Mato Grosso, Faculdade de Ciências Agrárias e Biológicas, Programa de Pós-Graduação em Ciências Ambientais. Cáceres, Mato Grosso, Brazil.ORCID http://orcid.org/0000-0001-7888-8183
Ednardo Fornanciari AntunesFaculdade do Pantanal, Cáceres, Mato Grosso, Brazil.ORCID http://orcid.org/0000-0003-4524-6576
Fabiana Gulin LonghiCentro de Excelência do Instituto Joanna Briggs, Centro Brasileiro para o Cuidado à Saúde Informado por Evidências, São Paulo, São Paulo, Brazil.ORCID http://orcid.org/0000-0001-6987-7271
Tatiane Amorim de MatosUniversidade do Estado de Mato Grosso, Faculdade de Ciências Agrárias e Biológicas, Programa de Pós-Graduação em Ciências Ambientais. Cáceres, Mato Grosso, Brazil.ORCID http://orcid.org/0000-0002-2898-1897
Paula Franciene BattagliniUniversidade Federal de Mato Grosso, Hospital Universitário Júlio Miller, Cuiabá, Mato Grosso, Brazil.ORCID http://orcid.org/0000-0001-7351-5257

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The new coronavirus, COVID-19 was declared a pandemic by the World Health Organization on March 11, 2020. Risk factors associated with this disease are age, sex, and the presence of comorbidities, the most common being hypertension, diabetes, and heart disease. The aim of this meta-analysis was to calculate the prevalence and geographical distribution of comorbidities in all patients admitted to intensive care units (ICUs), and the mortality rate of COVID-19. We selected studies based upon epidemiological and clinical descriptions of the patients and mortality from the disease to determine the pooled prevalence of comorbidities in all patients and in mortality cases due to COVID-19. The pooled prevalence was estimated using the random effects model, and odds ratios were used to measure the probability of death for a patient with a comorbidity. The total prevalence of comorbidities in patients with COVID-19 was 42% (95% CI: 25-60), 61% (95% CI: 42-80) in those admitted to the ICU, and 77% (95% CI: 68-86) among death cases; males were the most affected. Hypertension was the most prevalent comorbidity in all three groups studied, accounting for 32%, 26%, and 35%, respectively. The odds ratio of death for a patient with a comorbidity compared to one with no comorbidity was 2.4 (P < 0.0001). The higher the prevalence of comorbidities the higher the odds that the COVID-19 patient will need intensive care or will die, especially if the pre-existing disease is hypertension, heart disease, or diabetes.

Indexed as

BetacoronavirusComorbidityPandemicsCoronavirus InfectionsCOVID-19HumansPneumonia, ViralPrevalenceRisk FactorsSARS-CoV-2

Identifiers

PMID32578683
PMCPMC7310609

What OpenQuestion holds

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Registered trials

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.