Evidence map›Paper›PMID 41011817›Full record

ArticlePathogens (Basel, Switzerland)2025

Association Between Pre-Existing Conditions and COVID-19 Hospitalization, Intensive Care Services, and Mortality: A Cross-Sectional Analysis of an International Global Health Data Repository.

Basant M S Elsayed, Lina Altarawneh, Habib Hassan Farooqui, Muhammad Naseem Khan, Giridhara Rathnaiah Babu, Suhail A R Doi, Tawanda Chivese

Abstract read
In one paragraph

Article in Pathogens (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Basant M S ElsayedDepartment of Population Medicine, College of Medicine, QU Health, Qatar University, Doha 2713, Qatar.
Lina AltarawnehDepartment of Population Medicine, College of Medicine, QU Health, Qatar University, Doha 2713, Qatar.
Habib Hassan FarooquiDepartment of Population Medicine, College of Medicine, QU Health, Qatar University, Doha 2713, Qatar.ORCID 0000-0002-3081-2929
Muhammad Naseem KhanDepartment of Population Medicine, College of Medicine, QU Health, Qatar University, Doha 2713, Qatar.ORCID 0000-0002-0484-0985
Giridhara Rathnaiah BabuDepartment of Population Medicine, College of Medicine, QU Health, Qatar University, Doha 2713, Qatar.ORCID 0000-0003-4370-8933
Suhail A R DoiDepartment of Population Medicine, College of Medicine, QU Health, Qatar University, Doha 2713, Qatar.ORCID 0000-0002-2630-2125
Tawanda ChiveseDepartment of Science and Mathematics, School of Interdisciplinary Arts and Sciences, University of Washington Tacoma, Tacoma, Washington, WA 98402, USA.ORCID 0000-0001-6621-6144

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe use of globally shared individual-level data in answering epidemiological questions during health emergencies of international concern is still debatable. In this study, we investigated the association between pre-existing conditions and clinical outcomes of COVID-19 using data from a global data sharing repository.

methodsWe used data of all cases recorded in the Global Health Data repository up to the 10th of March 2021 to carry out a cross-sectional analysis of associations between cardiovascular diseases (CVD), hypertension, diabetes, obesity, lung diseases, and kidney disease and hospitalization, ICU admission, and mortality due to COVID-19. The Global Health repository reported data from 137 countries, but only Brazil, Mexico, and Cuba reported more than 10 COVID-19 cases in participants with preexisting conditions. We used multivariable logistic regression to compute adjusted odds ratios (aOR) of the three outcomes for each pre-existing condition in ten-year age groups from 0 to 9 years and up to 110-120 years.

findingsAs of March 10, the Global Health repository contained 25,900,000 records of confirmed cases of COVID-19, of which 2,900,000 cases from Brazil, Mexico, and Cuba had recorded data on pre-existing conditions. The overall aOR of ICU admission for each pre-existing condition were; CVD (aOR 2.1, 95%CI 1.8-2.4), hypertension (aOR 1.3, 95%CI 1.2-1.4), diabetes (OR 1.7, 95%CI 1.5-1.8), obesity (OR 2.2, 95%%CI 2.1-2.4), kidney disease (OR 1.4, 95%CI 1.2-1.7) and lung disease (aOR 1.1, 95%CI 0.9-1.3). Overall aORs of mortality for each pre-existing condition were: CVD (aOR 1.7, 95%CI 1.6-1.7), hypertension (aOR 1.3, 95%CI 1.3-1.4), diabetes (aOR 2.0, 95%CI 1.9-2.0), obesity (aOR 1.9, 95%CI 1.8-2.0), kidney disease (aOR 2.7, 95%CI 2.6-2.9), and lung disease (aOR 1.6, 95%CI 1.5-1.7). The odds of each adverse outcome were considerably larger in children and young adults with these preexisting conditions than for adults, especially for kidney disease, CVD, and diabetes.

conclusionThis analysis of a global health repository confirms associations between pre-existing diseases and clinical outcomes of COVID-19, and the odds of these outcomes were especially elevated in children and young adults with these preexisting conditions. This study shows that global data sharing can unlock answers to many epidemiological questions efficiently especially during the early stages of global health emergencies.

Indexed as

COVID-19Critical CareHospitalizationAdolescentAdultAgedAged, 80 and overBrazilCardiovascular DiseasesChildChild, PreschoolCross-Sectional StudiesFemaleGlobal HealthHumansInfantCOVID-19data sharingglobal healthhospitalizationintensive care unitmortalitypre-existing conditions

Identifiers

PMID41011817
PMCPMC12472582

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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.