Validation of sTREM-1 and IL-6 based algorithms for outcome prediction of COVID-19.
Détails
Télécharger: 37752433_BIB_F9BA2A5FEEC5.pdf (1189.56 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_F9BA2A5FEEC5
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Validation of sTREM-1 and IL-6 based algorithms for outcome prediction of COVID-19.
Périodique
BMC infectious diseases
ISSN
1471-2334 (Electronic)
ISSN-L
1471-2334
Statut éditorial
Publié
Date de publication
26/09/2023
Peer-reviewed
Oui
Volume
23
Numéro
1
Pages
630
Langue
anglais
Notes
Publication types: Journal Article ; Multicenter Study ; Observational Study
Publication Status: epublish
Publication Status: epublish
Résumé
A prospective observational cohort study of COVID-19 patients in a single Emergency Department (ED) showed that sTREM-1- and IL-6-based algorithms were highly predictive of adverse outcome (Van Singer et al. J Allergy Clin Immunol 2021). We aim to validate the performance of these algorithms at ED presentation.
This multicentric prospective observational study of PCR-confirmed COVID-19 adult patients was conducted in the ED of three Swiss hospitals. Data of the three centers were retrospectively completed and merged. We determined the predictive accuracy of the sTREM-1-based algorithm for 30-day intubation/mortality. We also determined the performance of the IL-6-based algorithm using data from one center for 30-day oxygen requirement.
373 patients were included in the validation cohort, 139 (37%) in Lausanne, 93 (25%) in St.Gallen and 141 (38%) in EOC. Overall, 18% (93/373) patients died or were intubated by day 30. In Lausanne, 66% (92/139) patients required oxygen by day 30. The predictive accuracy of sTREM-1 and IL-6 were similar compared to the derivation cohort. The sTREM-1-based algorithm confirmed excellent sensitivity (90% versus 100% in the derivation cohort) and negative predictive value (94% versus 100%) for 30-day intubation/mortality. The IL-6-based algorithm performance was acceptable with a sensitivity of 85% versus 98% in the derivation cohort and a negative predictive value of 60% versus 92%.
The sTREM-1 algorithm demonstrated good reproducibility. A prospective randomized controlled trial, comparing outcomes with and without the algorithm, is necessary to assess its safety and impact on hospital and ICU admission rates. The IL-6 algorithm showed acceptable validity in a single center and need additional validation before widespread implementation.
This multicentric prospective observational study of PCR-confirmed COVID-19 adult patients was conducted in the ED of three Swiss hospitals. Data of the three centers were retrospectively completed and merged. We determined the predictive accuracy of the sTREM-1-based algorithm for 30-day intubation/mortality. We also determined the performance of the IL-6-based algorithm using data from one center for 30-day oxygen requirement.
373 patients were included in the validation cohort, 139 (37%) in Lausanne, 93 (25%) in St.Gallen and 141 (38%) in EOC. Overall, 18% (93/373) patients died or were intubated by day 30. In Lausanne, 66% (92/139) patients required oxygen by day 30. The predictive accuracy of sTREM-1 and IL-6 were similar compared to the derivation cohort. The sTREM-1-based algorithm confirmed excellent sensitivity (90% versus 100% in the derivation cohort) and negative predictive value (94% versus 100%) for 30-day intubation/mortality. The IL-6-based algorithm performance was acceptable with a sensitivity of 85% versus 98% in the derivation cohort and a negative predictive value of 60% versus 92%.
The sTREM-1 algorithm demonstrated good reproducibility. A prospective randomized controlled trial, comparing outcomes with and without the algorithm, is necessary to assess its safety and impact on hospital and ICU admission rates. The IL-6 algorithm showed acceptable validity in a single center and need additional validation before widespread implementation.
Mots-clé
Adult, Humans, Algorithms, COVID-19/diagnosis, Interleukin-6, Prospective Studies, Reproducibility of Results, Retrospective Studies, Biomarkers, COVID-19, Clinical support decision tool, Validation study, sTREM-1
Pubmed
Web of science
Open Access
Oui
Création de la notice
29/09/2023 14:45
Dernière modification de la notice
08/08/2024 6:42