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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...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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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. |
format | Online Article Text |
id | pubmed-7867229 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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