Mar Riveiro-Barciela1,2,3, Moisés Labrador-Horrillo3,4,5, Laura Camps-Relats1, Didac González-Sans6, Meritxell Ventura-Cots1,2, María Terrones-Peinador6, Andrea Nuñez-Conde6, Mónica Martínez-Gallo3,7,8, Manuel Hernández3,7,8, Andrés Antón3,9, Antonio González6, Ricardo Pujol-Borrell3,7,8, Fernando Martínez-Valle3,6. 1. Liver Unit, Internal Medicine Department, Hospital Universitario Vall d'Hebrón, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain. 2. Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain. 3. Universitat Autònoma de Barcelona, Barcelona, Spain. 4. Allergy Section, Internal Medicine Department, Hospital Universitario Vall d'Hebrón, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain. 5. ARADyAL Research Network Instituto de Salud Carlos III, Madrid, Spain. 6. Systemic Autoimmune Diseases Unit, Internal Medicine Department, Hospital Universitario Vall d'Hebron, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain. 7. Diagnostic Immunology group, Vall d'Hebron Institut de Recerca (VHIR), Barcelona, Spain. 8. Division of Immunology, Department of Cell Biology Physiology and Immunology, Hospital Universitari Vall d'Hebron, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain. 9. Respiratory Viruses Unit, Microbiology Department, Hospital Universitari, Vall d'Hebron Vall d'Hebron Institut de recerca (VHIR), Barcelona Hospital Campus, Barcelona, Spain.
Abstract
BACKGROUND AND AIMS: Identification of SARS-CoV-2-infected patients at high-risk of poor prognosis is crucial. We aimed to establish predictive models for COVID-19 pneumonia severity in hospitalized patients. METHODS: Retrospective study of 430 patients admitted in Vall d'Hebron Hospital (Barcelona) between 03-12-2020 and 04-28-2020 due to COVID-19 pneumonia. Two models to identify the patients who required high-flow-oxygen-support were generated, one using baseline data and another with also follow-up analytical results. Calibration was performed by a 1000-bootstrap replication model. RESULTS: 249 were male, mean age 57.9 years. Overall, 135 (31.4%) required high-flow-oxygen-support. The baseline predictive model showed a ROC of 0.800 based on: SpO2/FiO2 (adjusted Hazard Ratio-aHR = 8), chest x-ray (aHR = 4), prior immunosuppressive therapy (aHR = 4), obesity (aHR = 2), IL-6 (aHR = 2), platelets (aHR = 0.5). The cut-off of 11 presented a specificity of 94.8%. The second model included changes on the analytical parameters: ferritin (aHR = 7.5 if ≥200ng/mL) and IL-6 (aHR = 18 if ≥64pg/mL) plus chest x-ray (aHR = 2) showing a ROC of 0.877. The cut-off of 12 exhibited a negative predictive value of 92%. CONCLUSIONS: SpO2/FiO2 and chest x-ray on admission or changes on inflammatory parameters as IL-6 and ferritin allow us early identification of COVID-19 patients at risk of high-flow-oxygen-support that may benefit from a more intensive disease management.
BACKGROUND AND AIMS: Identification of SARS-CoV-2-infectedpatients at high-risk of poor prognosis is crucial. We aimed to establish predictive models for COVID-19 pneumonia severity in hospitalized patients. METHODS: Retrospective study of 430 patients admitted in Vall d'Hebron Hospital (Barcelona) between 03-12-2020 and 04-28-2020 due to COVID-19 pneumonia. Two models to identify the patients who required high-flow-oxygen-support were generated, one using baseline data and another with also follow-up analytical results. Calibration was performed by a 1000-bootstrap replication model. RESULTS: 249 were male, mean age 57.9 years. Overall, 135 (31.4%) required high-flow-oxygen-support. The baseline predictive model showed a ROC of 0.800 based on: SpO2/FiO2 (adjusted Hazard Ratio-aHR = 8), chest x-ray (aHR = 4), prior immunosuppressive therapy (aHR = 4), obesity (aHR = 2), IL-6 (aHR = 2), platelets (aHR = 0.5). The cut-off of 11 presented a specificity of 94.8%. The second model included changes on the analytical parameters: ferritin (aHR = 7.5 if ≥200ng/mL) and IL-6 (aHR = 18 if ≥64pg/mL) plus chest x-ray (aHR = 2) showing a ROC of 0.877. The cut-off of 12 exhibited a negative predictive value of 92%. CONCLUSIONS:SpO2/FiO2 and chest x-ray on admission or changes on inflammatory parameters as IL-6 and ferritin allow us early identification of COVID-19patients at risk of high-flow-oxygen-support that may benefit from a more intensive disease management.
Authors: Adrián Sánchez-Montalvá; Daniel Álvarez-Sierra; Mónica Martínez-Gallo; Janire Perurena-Prieto; Iria Arrese-Muñoz; Juan Carlos Ruiz-Rodríguez; Juan Espinosa-Pereiro; Pau Bosch-Nicolau; Xavier Martínez-Gómez; Andrés Antón; Ferran Martínez-Valle; Mar Riveiro-Barciela; Albert Blanco-Grau; Francisco Rodríguez-Frias; Pol Castellano-Escuder; Elisabet Poyatos-Canton; Jordi Bas-Minguet; Eva Martínez-Cáceres; Alex Sánchez-Pla; Coral Zurera-Egea; Aina Teniente-Serra; Manuel Hernández-González; Ricardo Pujol-Borrell Journal: Front Immunol Date: 2022-06-29 Impact factor: 8.786
Authors: María C Martín; Aurora Jurado; Cristina Abad-Molina; Antonio Orduña; Oscar Yarce; Ana M Navas; Vanesa Cunill; Danilo Escobar; Francisco Boix; Sergio Burillo-Sanz; María C Vegas-Sánchez; Yesenia Jiménez-de Las Pozas; Josefa Melero; Marta Aguilar; Oana Irina Sobieschi; Marcos López-Hoyos; Gonzalo Ocejo-Vinyals; David San Segundo; Delia Almeida; Silvia Medina; Luis Fernández; Esther Vergara; Bibiana Quirant; Eva Martínez-Cáceres; Marc Boiges; Marta Alonso; Laura Esparcia-Pinedo; Celia López-Sanz; Javier Muñoz-Vico; Serafín López-Palmero; Antonio Trujillo; Paula Álvarez; Álvaro Prada; David Monzón; Jesús Ontañón; Francisco M Marco; Sergio Mora; Ricardo Rojo; Gema González-Martínez; María T Martínez-Saavedra; Juana Gil-Herrera; Sergi Cantenys-Molina; Manuel Hernández; Janire Perurena-Prieto; Beatriz Rodríguez-Bayona; Alba Martínez; Esther Ocaña; Juan Molina Journal: Immun Ageing Date: 2021-05-20 Impact factor: 6.400