Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

BACKGROUND: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. METHODS: Th...

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Detalles Bibliográficos
Autores principales: Kartsonaki, Christiana, Baillie, J Kenneth, Barrio, Noelia García, Baruch, Joaquín, Beane, Abigail, Blumberg, Lucille, Bozza, Fernando, Broadley, Tessa, Burrell, Aidan, Carson, Gail, Citarella, Barbara Wanjiru, Dagens, Andrew, Dankwa, Emmanuelle A, Donnelly, Christl A, Dunning, Jake, Elotmani, Loubna, Escher, Martina, Farshait, Nataly, Goffard, Jean-Christophe, Gonçalves, Bronner P, Hall, Matthew, Hashmi, Madiha, Sim Lim Heng, Benedict, Ho, Antonia, Jassat, Waasila, Pedrera Jiménez, Miguel, Laouenan, Cedric, Lissauer, Samantha, Martin-Loeches, Ignacio, Mentré, France, Merson, Laura, Morton, Ben, Munblit, Daniel, Nekliudov, Nikita A, Nichol, Alistair D, Singh Oinam, Budha Charan, Ong, David, Panda, Prasan Kumar, Petrovic, Michele, Pritchard, Mark G, Ramakrishnan, Nagarajan, Ramos, Grazielle Viana, Roger, Claire, Sandulescu, Oana, Semple, Malcolm G, Sharma, Pratima, Sigfrid, Louise, Somers, Emily C, Streinu-Cercel, Anca, Taccone, Fabio, Vecham, Pavan Kumar, Kumar Tirupakuzhi Vijayaraghavan, Bharath, Wei, Jia, Wils, Evert-Jan, Ci Wong, Xin, Horby, Peter, Rojek, Amanda, Olliaro, Piero L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Covid-19
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10114094/
https://www.ncbi.nlm.nih.gov/pubmed/36850054
http://dx.doi.org/10.1093/ije/dyad012
Descripción
Sumario:BACKGROUND: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. METHODS: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). RESULTS: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. CONCLUSIONS: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death.

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