1. Predicting critical illness on initial diagnosis of COVID-19 based on easily obtained clinical variables: development and validation of the PRIORITY model
- Author
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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 Manuel, 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, and UAM. Departamento de Medicina
- Subjects
Microbiology (medical) ,medicine.medical_specialty ,Evidence-based medicine ,Prognostic models ,Referral ,Medicina ,Critical Illness ,Logistic regression ,Initial assessment ,Risk Assessment ,law.invention ,law ,medicine ,Humans ,Medical history ,Generalizability theory ,Hospital Mortality ,Retrospective Studies ,business.industry ,Medicina basada en l'evidència ,COVID-19 ,Easily obtained clinical variables ,General Medicine ,Models, Theoretical ,medicine.disease ,Intensive care unit ,Confidence interval ,Hospitalization ,Infectious Diseases ,Spain ,Emergency medicine ,Cohort ,Critical illness ,business ,Kidney disease - 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., No funding was received for this work.
- Published
- 2021