dc.contributor.author | De Gonzalo-Calvo, David | |
dc.contributor.author | Molinero, Marta | |
dc.contributor.author | Benítez, Iván D. | |
dc.contributor.author | Martín Delgado, María Cruz | |
dc.contributor.author | Barbé, Ferran | |
dc.date.accessioned | 2024-02-28T19:59:03Z | |
dc.date.available | 2024-02-28T19:59:03Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 1465-9921 | spa |
dc.identifier.uri | https://hdl.handle.net/10641/4172 | |
dc.description.abstract | 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. | spa |
dc.language.iso | eng | spa |
dc.publisher | Respiratory Research | spa |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Biomarker | spa |
dc.subject | COVID-19 | spa |
dc.subject | MicroRNA | spa |
dc.subject | Prognosis | spa |
dc.subject | SARS-CoV-2 | spa |
dc.title | A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study. | spa |
dc.type | journal article | spa |
dc.type.hasVersion | AM | spa |
dc.rights.accessRights | open access | spa |
dc.description.extent | 3224 KB | spa |
dc.identifier.doi | 10.1186/s12931-023-02462-x | spa |
dc.relation.publisherversion | https://respiratory-research.biomedcentral.com/articles/10.1186/s12931-023-02462-x | spa |