Dataset Information

Clinical and Demographic Factors Associated With COVID-19, Severe COVID-19, and SARS-CoV-2 Infection in Adults: A Secondary Cross-Protocol Analysis of 4 Randomized Clinical Trials.

ABSTRACT:

SUBMITTER: Theodore DA

PROVIDER: S-EPMC10346130 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Clinical and Demographic Factors Associated With COVID-19, Severe COVID-19, and SARS-CoV-2 Infection in Adults: A Secondary Cross-Protocol Analysis of 4 Randomized Clinical Trials.

Theodore Deborah A DA Branche Angela R AR Zhang Lily L Graciaa Daniel S DS Choudhary Madhu M Hatlen Timothy J TJ Osman Raadhiya R Babu Tara M TM Robinson Samuel T ST Gilbert Peter B PB Follmann Dean D Janes Holly H Kublin James G JG Baden Lindsey R LR Goepfert Paul P Gray Glenda E GE Grinsztejn Beatriz B Kotloff Karen L KL Gay Cynthia L CL Leav Brett B Miller Jacqueline J Hirsch Ian I Sadoff Jerald J Dunkle Lisa M LM Neuzil Kathleen M KM Corey Lawrence L Falsey Ann R AR El Sahly Hana M HM Sobieszczyk Magdalena E ME Huang Yunda Y

JAMA network open 20230703 7

<h4>Importance</h4>Current data identifying COVID-19 risk factors lack standardized outcomes and insufficiently control for confounders.<h4>Objective</h4>To identify risk factors associated with COVID-19, severe COVID-19, and SARS-CoV-2 infection.<h4>Design, setting, and participants</h4>This secondary cross-protocol analysis included 4 multicenter, international, randomized, blinded, placebo-controlled, COVID-19 vaccine efficacy trials with harmonized protocols established by the COVID-19 Preve ...[more]

PMID: 37440227

Similar Datasets

Project description:BackgroundDrivers of COVID-19 severity are multifactorial and include multidimensional and potentially interacting factors encompassing viral determinants and host-related factors (i.e., demographics, pre-existing conditions and/or genetics), thus complicating the prediction of clinical outcomes for different severe acute respiratory syndrome coronavirus (SARS-CoV-2) variants. Although millions of SARS-CoV-2 genomes have been publicly shared in global databases, linkages with detailed clinical data are scarce. Therefore, we aimed to establish a COVID-19 patient dataset with linked clinical and viral genomic data to then examine associations between SARS-CoV-2 genomic signatures and clinical disease phenotypes.MethodsA cohort of adult patients with laboratory confirmed SARS-CoV-2 from 11 participating healthcare institutions in the Greater Toronto Area (GTA) were recruited from March 2020 to April 2022. Supervised machine learning (ML) models were developed to predict hospitalization using SARS-CoV-2 lineage-specific genomic signatures, patient demographics, symptoms, and pre-existing comorbidities. The relative importance of these features was then evaluated.ResultsComplete clinical data and viral whole genome level information were obtained from 617 patients, 50.4% of whom were hospitalized. Notably, inpatients were older with a mean age of 66.67 years (SD ± 17.64 years), whereas outpatients had a mean age of 44.89 years (SD ± 16.00 years). SHapley Additive exPlanations (SHAP) analyses revealed that underlying vascular disease, underlying pulmonary disease, and fever were the most significant clinical features associated with hospitalization. In models built on the amino acid sequences of functional regions including spike, nucleocapsid, ORF3a, and ORF8 proteins, variants preceding the emergence of variants of concern (VOCs) or pre-VOC variants, were associated with hospitalization.ConclusionsViral genomic features have limited utility in predicting hospitalization across SARS-CoV-2 diversity. Combining clinical and viral genomic datasets provides perspective on patient specific and virus-related factors that impact COVID-19 disease severity. Overall, clinical features had greater discriminatory power than viral genomic features in predicting hospitalization.

Dataset Information

Clinical and Demographic Factors Associated With COVID-19, Severe COVID-19, and SARS-CoV-2 Infection in Adults: A Secondary Cross-Protocol Analysis of 4 Randomized Clinical Trials.

Publications

Clinical and Demographic Factors Associated With COVID-19, Severe COVID-19, and SARS-CoV-2 Infection in Adults: A Secondary Cross-Protocol Analysis of 4 Randomized Clinical Trials.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets