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Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients

The mortality of COVID-19 patients in the intensive care unit (ICU) is influenced by their state at admission. We aimed to model COVID-19 acute respiratory distress syndrome state transitions from ICU admission to day 60 outcome and to evaluate possible prognostic factors. We analyzed a prospective...

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Autores principales: Ursino, Moreno, Dupuis, Claire, Buetti, Niccolò, de Montmollin, Etienne, Bouadma, Lila, Golgran-Toledano, Dany, Ruckly, Stéphane, Neuville, Mathilde, Cohen, Yves, Mourvillier, Bruno, Souweine, Bertrand, Gainnier, Marc, Laurent, Virginie, Terzi, Nicolas, Shiami, Shidasp, Reignier, Jean, Alberti, Corinne, Timsit, Jean-François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867229/
https://www.ncbi.nlm.nih.gov/pubmed/33540733
http://dx.doi.org/10.3390/jcm10030544
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author Ursino, Moreno
Dupuis, Claire
Buetti, Niccolò
de Montmollin, Etienne
Bouadma, Lila
Golgran-Toledano, Dany
Ruckly, Stéphane
Neuville, Mathilde
Cohen, Yves
Mourvillier, Bruno
Souweine, Bertrand
Gainnier, Marc
Laurent, Virginie
Terzi, Nicolas
Shiami, Shidasp
Reignier, Jean
Alberti, Corinne
Timsit, Jean-François
author_facet Ursino, Moreno
Dupuis, Claire
Buetti, Niccolò
de Montmollin, Etienne
Bouadma, Lila
Golgran-Toledano, Dany
Ruckly, Stéphane
Neuville, Mathilde
Cohen, Yves
Mourvillier, Bruno
Souweine, Bertrand
Gainnier, Marc
Laurent, Virginie
Terzi, Nicolas
Shiami, Shidasp
Reignier, Jean
Alberti, Corinne
Timsit, Jean-François
author_sort Ursino, Moreno
collection PubMed
description The mortality of COVID-19 patients in the intensive care unit (ICU) is influenced by their state at admission. We aimed to model COVID-19 acute respiratory distress syndrome state transitions from ICU admission to day 60 outcome and to evaluate possible prognostic factors. We analyzed a prospective French database that includes critically ill COVID-19 patients. A six-state multistate model was built and 17 transitions were analyzed either using a non-parametric approach or a Cox proportional hazard model. Corticosteroids and IL-antagonists (tocilizumab and anakinra) effects were evaluated using G-computation. We included 382 patients in the analysis: 243 patients were admitted to the ICU with non-invasive ventilation, 116 with invasive mechanical ventilation, and 23 with extracorporeal membrane oxygenation. The predicted 60-day mortality was 25.9% (95% CI: 21.8%–30.0%), 44.7% (95% CI: 48.8%–50.6%), and 59.2% (95% CI: 49.4%–69.0%) for a patient admitted in these three states, respectively. Corticosteroids decreased the risk of being invasively ventilated (hazard ratio (HR) 0.59, 95% CI: 0.39–0.90) and IL-antagonists increased the probability of being successfully extubated (HR 1.8, 95% CI: 1.02–3.17). Antiviral drugs did not impact any transition. In conclusion, we observed that the day-60 outcome in COVID-19 patients is highly dependent on the first ventilation state upon ICU admission. Moreover, we illustrated that corticosteroid and IL-antagonists may influence the intubation duration.
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spelling pubmed-78672292021-02-07 Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients Ursino, Moreno Dupuis, Claire Buetti, Niccolò de Montmollin, Etienne Bouadma, Lila Golgran-Toledano, Dany Ruckly, Stéphane Neuville, Mathilde Cohen, Yves Mourvillier, Bruno Souweine, Bertrand Gainnier, Marc Laurent, Virginie Terzi, Nicolas Shiami, Shidasp Reignier, Jean Alberti, Corinne Timsit, Jean-François J Clin Med Article The mortality of COVID-19 patients in the intensive care unit (ICU) is influenced by their state at admission. We aimed to model COVID-19 acute respiratory distress syndrome state transitions from ICU admission to day 60 outcome and to evaluate possible prognostic factors. We analyzed a prospective French database that includes critically ill COVID-19 patients. A six-state multistate model was built and 17 transitions were analyzed either using a non-parametric approach or a Cox proportional hazard model. Corticosteroids and IL-antagonists (tocilizumab and anakinra) effects were evaluated using G-computation. We included 382 patients in the analysis: 243 patients were admitted to the ICU with non-invasive ventilation, 116 with invasive mechanical ventilation, and 23 with extracorporeal membrane oxygenation. The predicted 60-day mortality was 25.9% (95% CI: 21.8%–30.0%), 44.7% (95% CI: 48.8%–50.6%), and 59.2% (95% CI: 49.4%–69.0%) for a patient admitted in these three states, respectively. Corticosteroids decreased the risk of being invasively ventilated (hazard ratio (HR) 0.59, 95% CI: 0.39–0.90) and IL-antagonists increased the probability of being successfully extubated (HR 1.8, 95% CI: 1.02–3.17). Antiviral drugs did not impact any transition. In conclusion, we observed that the day-60 outcome in COVID-19 patients is highly dependent on the first ventilation state upon ICU admission. Moreover, we illustrated that corticosteroid and IL-antagonists may influence the intubation duration. MDPI 2021-02-02 /pmc/articles/PMC7867229/ /pubmed/33540733 http://dx.doi.org/10.3390/jcm10030544 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ursino, Moreno
Dupuis, Claire
Buetti, Niccolò
de Montmollin, Etienne
Bouadma, Lila
Golgran-Toledano, Dany
Ruckly, Stéphane
Neuville, Mathilde
Cohen, Yves
Mourvillier, Bruno
Souweine, Bertrand
Gainnier, Marc
Laurent, Virginie
Terzi, Nicolas
Shiami, Shidasp
Reignier, Jean
Alberti, Corinne
Timsit, Jean-François
Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients
title Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients
title_full Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients
title_fullStr Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients
title_full_unstemmed Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients
title_short Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients
title_sort multistate modeling of covid-19 patients using a large multicentric prospective cohort of critically ill patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867229/
https://www.ncbi.nlm.nih.gov/pubmed/33540733
http://dx.doi.org/10.3390/jcm10030544
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