| Title: |
Exposing and Overcoming Limitations of Clinical Laboratory Tests in COVID-19 by Adding Immunological Parameters; A Retrospective Cohort Analysis and Pilot Study |
| Authors: |
Sánchez Montalvá, Adrián; Álvarez Sierra, Daniel; Martínez Gallo, Mónica; Perurena-Prieto, Janire; Arrese Muñoz, Iria; Ruiz Rodríguez, Juan Carlos; Espinosa Pereiro, Juan; Bosch Nicolau, Pau; Martínez Gómez, Xavier; Antón, Andrés; Martínez Valle, Ferran; Riveiro-Barciela, Mar; Blanco Grau, Albert; Rodríguez-Frías, Francisco; Castellano Escuder, Pol; Poyatos Canton, Elisabet; Bas Minguet, Jordi; Martínez Cáceres, Eva; Sánchez Pla, Alex; Zurera Egea, Coral; Teniente Serra, Aina; Hernández González, Manuel; Pujol Borrell, Ricardo; The Hospital Vall D’hebron Group for the study of Covid-19 Immune Profile |
| Source: |
Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL)) |
| Publisher Information: |
Frontiers Media SA |
| Publication Year: |
2022 |
| Collection: |
Dipòsit Digital de la Universitat de Barcelona |
| Subject Terms: |
COVID-19; Marcadors bioquímics; Citocines; Biochemical markers; Cytokines |
| Description: |
BackgroundTwo years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted for clinical management and in most algorithms the contribution of laboratory variables is limited. ObjectivesTo measure the predictive performance of currently used clinical laboratory tests alone or combined with clinical variables and explore the predictive power of immunological tests adequate for clinical laboratories. Methods: Data from 2,600 COVID-19 patients of the first wave of the pandemic in the Barcelona area (exploratory cohort of 1,579, validation cohorts of 598 and 423 patients) including clinical parameters and laboratory tests were retrospectively collected. 28-day survival and maximal severity were the main outcomes considered in the multiparametric classical and machine learning statistical analysis. A pilot study was conducted in two subgroups (n=74 and n=41) measuring 17 cytokines and 27 lymphocyte phenotypes respectively. Findings1) Despite a strong association of clinical and laboratory variables with the outcomes in classical pairwise analysis, the contribution of laboratory tests to the combined prediction power was limited by redundancy. Laboratory variables reflected only two types of processes: inflammation and organ damage but none reflected the immune response, one major determinant of prognosis. 2) Eight of the thirty variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the combined statistical predictive power. 3) The interpretation of clinical and laboratory variables was moderately improved by grouping them in two categories i.e., inflammation related biomarkers and organ damage related biomarkers; Age and organ damage-related biomarker tests were the best predictors of survival, and inflammatory-related ones were the best predictors of severity. 4) The pilot study ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
19 p.; application/pdf |
| Language: |
English |
| Relation: |
Reproducció del document publicat a: https://doi.org/10.3389/fimmu.2022.902837; Frontiers in Immunology, 2022, vol. 13, num. 902837; https://doi.org/10.3389/fimmu.2022.902837; https://hdl.handle.net/2445/188703 |
| Availability: |
https://hdl.handle.net/2445/188703 |
| Rights: |
cc by (c) Sánchez Montalvá, Adrián et al., 2022 ; http://creativecommons.org/licenses/by/3.0/es/ ; info:eu-repo/semantics/openAccess |
| Accession Number: |
edsbas.97D1F0D6 |
| Database: |
BASE |