Evidence map›Paper›PMID 33051749›Full record

ArticleJournal of racial and ethnic health disparities2021

Risk Factors Associated with Mortality Among Patients with Novel Coronavirus Disease (COVID-19) in Africa.

Mustapha Mohammed, Surajuddeen Muhammad, Fatima Zaji Mohammed, Sagir Mustapha, Abubakar Sha'aban, Najib Yahaya Sani, Mubarak Hussaini Ahmad, Auwal Adam Bala, Marzuq Abubakar Ungogo, Nawaf M Alotaibi and 1 more

Abstract read
In one paragraph

Article in Journal of racial and ethnic health disparities, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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.

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

15 citing papers in PubMed.

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  7. The Management of Myocardial Injury Related to SARS-CoV-2 Pneumonia.Journal of cardiovascular development and disease · 2022
    Review
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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

11 authors.

Mustapha MohammedSchool of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Pulau Pinang, Malaysia. macreener88@gmail.com.ORCID 0000-0002-5021-1610
Surajuddeen MuhammadFaculty of Veterinary Medicine, Ahmadu Bello University, Zaria, Kaduna, Nigeria.ORCID 0000-0001-8567-0748
Fatima Zaji MohammedSchool of Dental Health Sciences, Shehu Idris College of Health Sciences and Technology, Makarfi, Kaduna, Nigeria.ORCID 0000-0002-7775-4463
Sagir MustaphaSchool of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.ORCID 0000-0003-4185-1680
Abubakar Sha'abanSchool of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Pulau Pinang, Malaysia.ORCID 0000-0002-5491-9851
Najib Yahaya SaniCenter for Drug Research, Universiti Sains Malaysia, Penang, Pulau Pinang, Malaysia.ORCID 0000-0003-3076-3706
Mubarak Hussaini AhmadDepartment of Pharmacology and Therapeutics, Ahmadu Bello University, Zaria, Kaduna, Nigeria.ORCID 0000-0003-1721-5481
Auwal Adam BalaDepartment of Pharmacology, College of Medicine and Health Sciences, Federal University Dutse, Jigawa, Nigeria.ORCID 0000-0003-0402-9639
Marzuq Abubakar UngogoDepartment of Veterinary Pharmacology and Toxicology, Ahmadu Bello University, Zaria, Nigeria.ORCID 0000-0003-4918-1423
Nawaf M AlotaibiCollege of Pharmacy, Northern Border University, Rafha, Kingdom of Saudi Arabia.ORCID 0000-0002-2170-0335
Hadzliana ZainalSchool of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Pulau Pinang, Malaysia.ORCID 0000-0001-6263-4824

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in China and later spread rapidly to other parts of the world, including Africa. Africa was projected to be devastated by COVID-19. There is currently limited data regarding regional predictors of mortality among patients with COVID-19. This study aimed to evaluate the independent risk factors associated with mortality among patients with COVID-19 in Africa.

methodsA total of 1028 confirmed cases of COVID-19 from Africa with definite survival outcomes were identified retrospectively from an open-access individual-level worldwide COVID-19 database. The live version of the dataset is available at https://github.com/beoutbreakprepared/nCoV2019 . Multivariable logistic regression was conducted to determine the risk factors that independently predict mortality among patients with COVID-19 in Africa.

resultsOf the 1028 cases included in study, 432 (42.0%) were females with a median (interquartile range, IQR) age of 50 (24) years. Older age (adjusted odds ratio {aOR} 1.06; [95% confidence intervals {95% CI}, 1.04-1.08]), presence of chronic disease (aOR 9.63; [95% CI, 3.84-24.15]), travel history (aOR 2.44; [95% CI, 1.26-4.72]), as well as locations of Central Africa (aOR 0.14; [95% CI, 0.03-0.72]) and West Africa (aOR 0.12; [95% CI, 0.04-0.32]) were identified as the independent risk factors significantly associated with increased mortality among the patients with COVID-19.

conclusionsThe COVID-19 pandemic is evolving gradually in Africa. Among patients with COVID-19 in Africa, older age, presence of chronic disease, travel history, and the locations of Central Africa and West Africa were associated with increased mortality. A regional response should prioritize strategies that will protect these populations. Also, conducting a further in-depth study could provide more insights into additional factors predictive of mortality in COVID-19 patients.

Indexed as

Health Status DisparitiesHospital MortalityAdultAfricaAgedCOVID-19FemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsAfricaCOVID-19MortalityPandemicRisk factorsSARS-COV-2

Identifiers

PMID33051749
PMCPMC7553376

What OpenQuestion holds

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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.