dc.contributor.author | Barrio Beraza, Irantzu | |
dc.contributor.author | COVID-Health Basque Country Research Group | |
dc.date.accessioned | 2023-04-25T17:45:50Z | |
dc.date.available | 2023-04-25T17:45:50Z | |
dc.date.issued | 2023-05 | |
dc.identifier.citation | International Journal of Medical Informatics 173 : (2023) // Article ID 105039 | es_ES |
dc.identifier.issn | 1386-5056 | |
dc.identifier.issn | 1872-8243 | |
dc.identifier.uri | http://hdl.handle.net/10810/60926 | |
dc.description.abstract | Objective
We identify factors related to SARS-CoV-2 infection linked to hospitalization, ICU admission, and mortality and develop clinical prediction rules.
Methods
Retrospective cohort study of 380,081 patients with SARS-CoV-2 infection from March 1, 2020 to January 9, 2022, including a subsample of 46,402 patients who attended Emergency Departments (EDs) having data on vital signs. For derivation and external validation of the prediction rule, two different periods were considered: before and after emergence of the Omicron variant, respectively. Data collected included sociodemographic data, COVID-19 vaccination status, baseline comorbidities and treatments, other background data and vital signs at triage at EDs. The predictive models for the EDs and the whole samples were developed using multivariate logistic regression models using Lasso penalization.
Results
In the multivariable models, common predictive factors of death among EDs patients were greater age; being male; having no vaccination, dementia; heart failure; liver and kidney disease; hemiplegia or paraplegia; coagulopathy; interstitial pulmonary disease; malignant tumors; use chronic systemic use of steroids, higher temperature, low O2 saturation and altered blood pressure-heart rate. The predictors of an adverse evolution were the same, with the exception of liver disease and the inclusion of cystic fibrosis. Similar predictors were found to be related to hospital admission, including liver disease, arterial hypertension, and basal prescription of immunosuppressants. Similarly, models for the whole sample, without vital signs, are presented.
Conclusions
We propose risk scales, based on basic information, easily-calculable, high-predictive that also function with the current Omicron variant and may help manage such patients in primary, emergency, and hospital care. | es_ES |
dc.description.sponsorship | This work was supported in part by the health outcomes group from Galdakao-Barrualde Health Organization; the Kronikgune Institute for Health Service Research; and the thematic network–REDISSEC (Red de Investigación en Servicios de Salud en Enfermedades Crónicas)–of the Instituto de Salud Carlos III. The work of IB was financially supported in part by grants from the Departamento de Educación, Política Lingüística y Cultura del Gobierno Vasco [IT1456-22] and by the Ministry of Science and Innovation through BCAM Severo Ochoa accreditation [CEX2021-001142-S/MICIN/AEI/10.13039/501100011033] and through project [PID2020-115882RB-I00/AEI/10.13039/501100011033] funded by Agencia Estatal de Investigación and acronym “S3M1P4R” and also by the Basque Government through the BERC 2022–2025 program and the BMTF ‘‘Mathematical Modeling Applied to Health’’ Project. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/CEX2021-001142-S | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/PID2020-115882RB-I00 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | SARS-CoV-2 | es_ES |
dc.subject | COVID-19 | es_ES |
dc.subject | clinical decision rules | es_ES |
dc.subject | outcome assessment | es_ES |
dc.subject | health care | es_ES |
dc.title | Clinical prediction rules for adverse evolution in patients with COVID-19 by the Omicron variant | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S1386505623000576?via%3Dihub | es_ES |
dc.identifier.doi | 10.1016/j.ijmedinf.2023.105039 | |
dc.departamentoes | Matemáticas | es_ES |
dc.departamentoeu | Matematika | es_ES |