Evidence map›Paper›PMID 33101547›Full record

ReviewEuropean journal of integrative medicine2020

Predictors of mortality in patients with COVID-19-a systematic review.

Esmaeil Mehraeen, Amirali Karimi, Alireza Barzegary, Farzin Vahedi, Amir Masoud Afsahi, Omid Dadras, Banafsheh Moradmand-Badie, Seyed Ahmad Seyed Alinaghi, Shayesteh Jahanfar

Registry-linked trialAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in European journal of integrative medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04659876 (Clinical Characteristics and Laboratory Values Affecting Mortality in Critical Coronavirus Disease 2019 Patients Followed in the Intensive Care Unit), which is not on this map. Cited by 99 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed, 11 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.

NCT04659876 completednot on this map

Clinical Characteristics and Laboratory Values Affecting Mortality in Critical Coronavirus Disease 2019 Patients Followed in the Intensive Care Unit

TypeobservationalSponsorSaglik Bilimleri Universitesi Gazi Yasargil Training and Research HospitalRan2020 to 2020Enrolled445ConditionsCovid19 and MortalityArmsclinical features and laboratory values
3 · Its place in the literature

Who cites it

99 citing papers in PubMed, 11 syntheses or guidelines pooled it.

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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

9 authors.

Esmaeil MehraeenDepartment of Health Information Technology, Khalkhal University of Medical Sciences, Khalkhal, Iran.
Amirali KarimiSchool of medicine, Tehran University of Medical Sciences, Tehran, Iran.
Alireza BarzegarySchool of medicine, Islamic Azad University, Tehran, Iran.
Farzin VahediSchool of medicine, Tehran University of Medical Sciences, Tehran, Iran.
Amir Masoud AfsahiDepartment of Radiology, School of Medicine, University of California, San Diego (UCSD), CA, United States.
Omid DadrasDepartment of Global Health and Socioepidemiology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Banafsheh Moradmand-BadieBlack Dog Institute, University of New South Wales, Sydney, Australia.
Seyed Ahmad Seyed AlinaghiIranian Research Center for HIV/AIDS, Iranian Institute for Reduction of High Risk Behaviors, Tehran University of Medical Sciences, Tehran, Iran.
Shayesteh JahanfarSchool of Public Health, Central Michigan University, Mount Pleasant, MI, 48859, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn the current COVID-19 pandemic, disease diagnosis is essential for optimal management and timely isolation of infected cases in order to prevent further spread. The aim of this study was to systematically review the assessment of risk and model the predictors of mortality in COVID-19 patients.

methodsA systematic search was conducted of PubMed, Scopus, Embase, Google Scholar, and Web of Science databases. Variables associated with hospital mortality using bivariate analysis were included as potential independent predictors associated with mortality at the

resultsWe included 114 studies accounting for 310,494 patients from various parts of the world. For the purpose of this analysis, we set a cutoff point of 10% for the mortality percentages. High mortality rates were defined as higher than 10% of confirmed positive cases and were given a score of two, while low mortality (<10%) was assigned the score of one. We then analyzed the associations between 72 variables and the observed mortality rates. These variables included a large range of related variables such as demographics, signs and symptoms and related morbidities, vital signs, laboratory findings, imaging studies, underlying diseases, and the status of countries' income, based on the United Nation's classifications.

conclusionFindings suggest that older age, hypertension, and diabetes mellitus conferred a significant increased risk of mortality among patients with COVID-19. In the multivariate analysis, only diabetes mellitus demonstrated an independent relationship with increased mortality. Further studies are needed to ascertain the relationship between possible risk factors with COVID-19 mortality.

Indexed as

COVID-19ModelingMortalityPredictorsRisk factorsSystematic review

Identifiers

PMID33101547
PMCPMC7568488

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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.