A transfer triage tool for COVID-19 mass critical care surges

The objective of this study is to develop and validate a predictive model for mortality among severe COVID-19 patients who are candidates for inter-hospital transfer. A multicenter prospective observational study was conducted between 1 January 2021 and 30 April 2021 (third and fourth pandemic waves) in regional coordination centers of the Emergency Medical Services of eight Spanish autonomous communities. Hospitalized patients with severe COVID-19 transferred to other hospitals were included. Clinical variables from the initial evaluation, the triage score, and in-hospital mortality rates were collected. A Lasso-type regression analysis was performed to fit the mortality predictive model and its performance was evaluated by a leave-one-out cross-validation. Subsequently, the regional mass triage (MATER) score was created. 1,018 transferred patients were included, with a mean age of 62.3 years (SD 12), of whom 65.1% were male and 89.6% were admitted to an Intensive Care Unit. In-hospital mortality was 23.0%. The MATER score included six variables and presented good discrimination ability with an area under the curve of 0.79 (95% CI 0.77-0.81) and a good calibration with a Brier score of 0.135. The MATER score successfully predicted the mortality rate of severe COVID-19 patients and can be helpful in decision-making for triage and transfer prioritization in mass critical care surges.

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Publication Details

Journal
Scientific Reports
Published
2025-04-05
DOI
https://doi.org/10.1038/s41598-025-95337-8
Citations
1
Primary Topic
Disaster Response and Management
Type
article
Field-Weighted Citation Impact
2.52
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article

A transfer triage tool for COVID-19 mass critical care surges

E. J. Villalba, Youcef Azeli, Mario Toboso Martín, Amanda Bermejo et al.
1 citations
Scientific Reports
Disaster Response and Management
2.52
article

A transfer triage tool for COVID-19 mass critical care surges

E. J. Villalba, Youcef Azeli, Mario Toboso Martín, Amanda Bermejo, Marta Cubedo, I Fontan, Jorge Morales-Alvarez, Rafael Castro Delgado, Ricardo Vivancos Delgado, Cristina Solano Goñi, Steffen T. Simon, Silvia Solà-Muñoz, María José Luque‐Hernández, Raquel Abejón, Edurne Miren Mugica, Maria Ángeles Soto-García, Tatiana Cuartas-Álvarez, Josep Trenado, Javier Jacob, Xavier Jiménez-Fàbrega, Cristina López-López, Maria Del Mar Carricondo-Avivar, María Elena Castejón, César Cardenete, Zita Quintela, Antonio Bracero
article en
1 citations

Abstract

The objective of this study is to develop and validate a predictive model for mortality among severe COVID-19 patients who are candidates for inter-hospital transfer. A multicenter prospective observational study was conducted between 1 January 2021 and 30 April 2021 (third and fourth pandemic waves) in regional coordination centers of the Emergency Medical Services of eight Spanish autonomous communities. Hospitalized patients with severe COVID-19 transferred to other hospitals were included. Clinical variables from the initial evaluation, the triage score, and in-hospital mortality rates were collected. A Lasso-type regression analysis was performed to fit the mortality predictive model and its performance was evaluated by a leave-one-out cross-validation. Subsequently, the regional mass triage (MATER) score was created. 1,018 transferred patients were included, with a mean age of 62.3 years (SD 12), of whom 65.1% were male and 89.6% were admitted to an Intensive Care Unit. In-hospital mortality was 23.0%. The MATER score included six variables and presented good discrimination ability with an area under the curve of 0.79 (95% CI 0.77-0.81) and a good calibration with a Brier score of 0.135. The MATER score successfully predicted the mortality rate of severe COVID-19 patients and can be helpful in decision-making for triage and transfer prioritization in mass critical care surges.

Scientific ReportsVol. 15(1)
Universidad de Oviedo (ES), Universidad de La Rioja (ES), Gobierno del Principado de Asturias (ES), Bellvitge University Hospital (ES), Servicio Navarro de Salud (ES), University Hospital Mútua de Terrassa (ES), Institut de Recerca Biomèdica Catalunya Sud (ES), Ajuntament de L’Hospitalet (ES), Institut Català d'Oncologia (ES), Madrid Health Service (ES), Hospital Universitario Reina Sofía (ES), Osakidetza (ES), Servicio de Salud de Castilla La Mancha (ES), Centro de Emergencias Sanitarias 061 (ES), Hospital Universitari Sant Joan de Reus (ES), Gobierno de La Rioja (ES), Universitat de les Illes Balears (ES), Universitat de Barcelona (ES)
Openalex Percentile: Top 15%
Disaster Response and Management
2.52
DOIOpen Access PDFOpenAlex
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