Development and validation of a clinical score to estimate progression to severe or critical state in COVID-19 pneumonia hospitalized patients
Year: 2020
Type: article
Study design: Observational Study
Abstract: The prognosis of a patient with Covid-19 pneumonia is uncertain. Our objective was to establish a predictive model of disease progression to facilitate early decision-making.A retrospective study was performed of patients admitted with Covid-19 pneumonia, classified as severe (admission to the intensive care unit, mechanic invasive ventilation, or death) or non-severe. A predictive model based on clinical, analytical, and radiological parameters was built. The probability of progression to severe disease was estimated by logistic regression analysis. Calibration and discrimination (receiver operating characteristics curves and AUC) were assessed to determine model performance.During the study period 1,152 patients presented with Covid-19 infection, of whom 229 (19.9%) were admitted for pneumonia. During hospitalization, 51 (22.3%) progressed to severe disease, of whom 26 required ICU care (11.4); 17 (7.4%) underwent invasive mechanical ventilation, and 32 (14%) died of any cause. Five predictors determined within 24 hours of admission were identified: Diabetes, Age, Lymphocyte count, SaO2, and pH (DALSH score). The prediction model showed a good clinical performance, including discrimination (AUC 0.87 CI 0.81, 0.92) and calibration (Brier score = 0.11). In total, 0%, 12%, and 50% of patients with severity risk scores ≤5%, 6-25%, and >25% exhibited disease progression, respectively.A simple risk score based on five factors predicts disease progression and facilitates early decision-making according to prognosis.
Source: Scientific Reports
Authors: Francisco Gude, Vanessa Riveiro, Nuria Rodríguez-Núñez, Jorge Ricoy, Óscar Lado-Baleato, Tamara Lourido, Carlos Rábade, Adriana Lama, Ana Casal, Romina Abelleira-París, Lucía Ferreiro, Juan Suárez-Antelo, María E. Toubes, Cristina Pou, Manuel Taboada-Muñiz, Felipe Calle-Velles, Plácido Mayán-Conesa, María L. Pérez del Molino, Cristóbal Galbán-Rodríguez, Julián Álvarez-Escudero, Carmen Beceiro-Abad, Sonia Molinos-Castro, Néstor Agra-Vázquez, María Pazo-Núñez, Emilio Páez-Guillán, Pablo Varela-García, Carmen Martínez-Rey, Hadrián Pernas-Pardavila, María J. Domínguez-Santalla, Martín Vidal-Vázquez, Ana T. Marques-Afonso, Arturo González-Quintela, José R. González-Juanatey, Antonio Pose, Luis Valdés
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,870
OpenAlex ID: W3045717469