RT journal article
T1 A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
A1 de Gonzalo Calvo, David
A1 Molinero, Marta
A1 Benítez, Iván D.
A1 Perez Pons, Manel
A1 García Mateo, Nadia
A1 Ortega, Alicia
A1 Postigo, Tamara
A1 García Hidalgo, María C.
A1 Belmonte, Thalía
A1 Rodríguez Muñoz, Carlos
A1 González, Jessica
A1 Torres, Gerard
A1 Gort Paniello, Clara
A1 Moncusí Moix, Anna
A1 Estella García, Ángel
A1 Tamayo Lomas, Luis
A1 Martínez de la Gándara, Amalia
A1 Socias, Lorenzo
A1 Peñasco, Yhivian
A1 de la Torre, María del Carmen
A1 Bustamante Munguira, Elena
A1 Gallego Curto, Elena
A1 Martínez Varela, Ignacio
A1 Martín Delgado, María Cruz
A1 Vidal Cortés, Pablo
A1 López Messa, Juan
A1 Pérez García, Felipe
A1 Caballero, Jesús
A1 Añón, José Manuel
A1 Loza Vázquez, Ana
A1 Carbonell, Nieves
A1 Marin Corral, Judith
A1 Jorge García, Ruth Noemí
A1 Barberà, Carmen
A1 Ceccato, Adrián
A1 Fernández Barat, Laia
A1 Ferrer, Ricard
A1 García Gasulla, Dario
A1 Lorente Balanza, Jose Ángel
A1 Menéndez, Rosario
A1 Motos, Ana
A1 Peñuelas, Oscar
A1 Riera, Jordi
A1 Bermejo Martin, Jesús F.
A1 Torres, Antoni
A1 Barbé, Ferrán
A2 Medicina
K1 COVID-19
K1 Biomarker
K1 ICU
K1 microRNA
K1 Prognosis
K1 SARS-CoV-2
AB Background: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. Methods: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. Results: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. Conclusions: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.
PB Springer
SN 1465-9921
YR 2023
FD 2023-06-17
LK http://hdl.handle.net/10498/29728
UL http://hdl.handle.net/10498/29728
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 08-nov-2026