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Title: | Predicting critical illness on initial diagnosis of COVID-19 based on easily obtained clinical variables: development and validation of the PRIORITY model |
Author: | Martínez Lacalzada, Miguel Viteri Noël, Adrián Manzano Espinosa, Luis Fabregate, Martin Rubio Rivas, Manuel Luis García, Sara Arnalich Fernández, Francisco Beato Pérez, José Luis Vargas Núñez, Juan Antonio Calvo, Elpidio Espiño Álvarez, Alexia Constanza Freire Castro, Santiago J. Loureiro Amigo, Jose Pesqueira Fontan, Paula Maria Pina, Adela Álvarez Suárez, Ana María Silva Asiain, Andrea García López, Beatriz Luque del Pino, Jairo Sanz Cánovas, Jaime Chazarra Pérez, Paloma García García, Gema María Núñez Cortés, Jesús Millán Casas Rojo, José Manuel Gómez Huelgas, Ricardo Abrego Vaca, Luis F. Andreu Arnanz, Ana Arce García, Octavio A. Bajo González, Marta Borque Sanz, Pablo Cózar Llistó, Alberto Hoyo Cuenda, Beatriz del Gamboa Osorio, Alejandra García Sánchez, Isabel López Cisneros, Óscar A. Merino Ortiz, Borja Riera González, Elisa Rey García, Jimena Sánchez Díaz, Cristina Starita Fajardo, Grisell Suárez Carantoña, Cecilia Zhilina Zhilina, Svetlana SEMI-COVID-19 Network |
Keywords: | COVID-19 Medicina basada en l'evidència COVID-19 Evidence-based medicine |
Issue Date: | 1-Jul-2021 |
Publisher: | Elsevier BV |
Abstract: | Objectives: We aimed to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of coronavirus disease 2019 (COVID-19), to identify patients at risk of critical outcomes. Methods: We used data from the SEMI-COVID-19 Registry, a cohort of consecutive patients hospitalized for COVID-19 from 132 centres in Spain (23rd March to 21st May 2020). For the development cohort, tertiary referral hospitals were selected, while the validation cohort included smaller hospitals. The primary outcome was a composite of in-hospital death, mechanical ventilation, or admission to intensive care unit. Clinical signs and symptoms, demographics, and medical history ascertained at presentation were screened using least absolute shrinkage and selection operator, and logistic regression was used to construct the predictive model. Results: There were 10 433 patients, 7850 in the development cohort (primary outcome 25.1%, 1967/7850) and 2583 in the validation cohort (outcome 27.0%, 698/2583). The PRIORITY model included: age, dependency, cardiovascular disease, chronic kidney disease, dyspnoea, tachypnoea, confusion, systolic blood pressure, and SpO2 ≤93% or oxygen requirement. The model showed high discrimination for critical illness in both the development (C-statistic 0.823; 95% confidence interval (CI) 0.813, 0.834) and validation (C-statistic 0.794; 95%CI 0.775, 0.813) cohorts. A freely available web-based calculator was developed based on this model (https://www.evidencio.com/models/show/2344). Conclusions: The PRIORITY model, based on easily obtained clinical information, had good discrimination and generalizability for identifying COVID-19 patients at risk of critical outcomes. |
Note: | Reproducció del document publicat a: https://doi.org/10.1016/j.cmi.2021.07.006 |
It is part of: | Clinical Microbiology and Infection, 2021, vol. 27, num. 12, p. 1838-1844 |
URI: | http://hdl.handle.net/2445/181831 |
Related resource: | https://doi.org/10.1016/j.cmi.2021.07.006 |
ISSN: | 1469-0691 |
Appears in Collections: | Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL)) |
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