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

F-CRIN PARTNERS Platform, AP-HP, Université de Paris, Inserm, F-75010 Paris, France
INSERM, Centre de Recherche des Cordeliers, Sorbonne Université, USPC, Université de Paris, F-75006 Paris, France
Medical Intensive Care Unit, Gabriel Montpied University Hospital, 63000 Clermont-Ferrand, France
Inserm U 1137, Université de Paris, Sorbonne Paris Cite, 75870 Paris, France
APHP, Medical and Infectious Diseases Intensive Care Unit, Bichat-Claude Bernard Hospital, 75018 Paris, France
Polyvalent ICU, Groupe Hospitalier Intercommunal Le Raincy Montfermeil, 93370 Montfermeil, France
ICUREsearch, Statistical Department, 38160 Saint Marcellin, France
Polyvalent ICU, Hôpital Foch, 92150 Suresnes, France
Intensive Care Unit, CHU Avicenne, Groupe Hospitalier Paris Seine Saint-Denis, AP-HP, 93000 Bobigny, France
UFR SMBH, Université Sorbonne Paris Nord, 93000 Bobigny, France
INSERM, U942, F-75010, 75010 Paris, France
Medical Intensive Care Unit, Robert Debré University Hospital, 51100 Reims, France
Service de Médecine Intensive Réanimation, La Timone 2 University Hospital, 13385 Marseille, France
Medical-Surgical Intensive Care Unit, André Mignot Hospital, 78150 Le Chesnay, France
INSERM, U1042, Université Grenoble-Alpes, HP2, 38000 Grenoble, France
Médecine Intensive Réanimation, CHU Grenoble-Alpes, 38700 Grenoble, France
Polyvalent ICU, Centre Hospitalier Sud Essonne Dourdan-Etampes, 91410 Dourdan, France
Service de Médecine Intensive Réanimation, CHU de Nantes, 44000 Nantes, France
Université de Paris, ECEVE, UMR 1123, Inserm, F-75010 Paris, France
Author to whom correspondence should be addressed.
Group email: [email protected]. All members are cited in the Acknowledgement section.
Academic Editor: Michael A. Froelich
J. Clin. Med. 2021, 10(3), 544;
Received: 12 December 2020 / Revised: 12 January 2021 / Accepted: 26 January 2021 / Published: 2 February 2021
(This article belongs to the Special Issue Management of Acute Respiratory Failure)
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. View Full-Text
Keywords: intensive unit care; acute respiratory distress disease; survival intensive unit care; acute respiratory distress disease; survival
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MDPI and ACS Style

Ursino, M.; Dupuis, C.; Buetti, N.; de Montmollin, E.; Bouadma, L.; Golgran-Toledano, D.; Ruckly, S.; Neuville, M.; Cohen, Y.; Mourvillier, B.; Souweine, B.; Gainnier, M.; Laurent, V.; Terzi, N.; Siami, S.; Reignier, J.; Alberti, C.; Timsit, J.-F.; on behalf of the OUTCOMEREA Study Group. Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients. J. Clin. Med. 2021, 10, 544.

AMA Style

Ursino M, Dupuis C, Buetti N, de Montmollin E, Bouadma L, Golgran-Toledano D, Ruckly S, Neuville M, Cohen Y, Mourvillier B, Souweine B, Gainnier M, Laurent V, Terzi N, Siami S, Reignier J, Alberti C, Timsit J-F, on behalf of the OUTCOMEREA Study Group. Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients. Journal of Clinical Medicine. 2021; 10(3):544.

Chicago/Turabian Style

Ursino, Moreno, Claire Dupuis, Niccolò Buetti, Etienne de Montmollin, Lila Bouadma, Dany Golgran-Toledano, Stéphane Ruckly, Mathilde Neuville, Yves Cohen, Bruno Mourvillier, Bertrand Souweine, Marc Gainnier, Virginie Laurent, Nicolas Terzi, Shidasp Siami, Jean Reignier, Corinne Alberti, Jean-François Timsit, and on behalf of the OUTCOMEREA Study Group. 2021. "Multistate Modeling of COVID-19 Patients Using a Large Multicentric Prospective Cohort of Critically Ill Patients" Journal of Clinical Medicine 10, no. 3: 544.

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