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Article

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

1
F-CRIN PARTNERS Platform, AP-HP, Université de Paris, Inserm, F-75010 Paris, France
2
INSERM, Centre de Recherche des Cordeliers, Sorbonne Université, USPC, Université de Paris, F-75006 Paris, France
3
Medical Intensive Care Unit, Gabriel Montpied University Hospital, 63000 Clermont-Ferrand, France
4
Inserm U 1137, Université de Paris, Sorbonne Paris Cite, 75870 Paris, France
5
APHP, Medical and Infectious Diseases Intensive Care Unit, Bichat-Claude Bernard Hospital, 75018 Paris, France
6
Polyvalent ICU, Groupe Hospitalier Intercommunal Le Raincy Montfermeil, 93370 Montfermeil, France
7
ICUREsearch, Statistical Department, 38160 Saint Marcellin, France
8
Polyvalent ICU, Hôpital Foch, 92150 Suresnes, France
9
Intensive Care Unit, CHU Avicenne, Groupe Hospitalier Paris Seine Saint-Denis, AP-HP, 93000 Bobigny, France
10
UFR SMBH, Université Sorbonne Paris Nord, 93000 Bobigny, France
11
INSERM, U942, F-75010, 75010 Paris, France
12
Medical Intensive Care Unit, Robert Debré University Hospital, 51100 Reims, France
13
Service de Médecine Intensive Réanimation, La Timone 2 University Hospital, 13385 Marseille, France
14
Medical-Surgical Intensive Care Unit, André Mignot Hospital, 78150 Le Chesnay, France
15
INSERM, U1042, Université Grenoble-Alpes, HP2, 38000 Grenoble, France
16
Médecine Intensive Réanimation, CHU Grenoble-Alpes, 38700 Grenoble, France
17
Polyvalent ICU, Centre Hospitalier Sud Essonne Dourdan-Etampes, 91410 Dourdan, France
18
Service de Médecine Intensive Réanimation, CHU de Nantes, 44000 Nantes, France
19
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; https://doi.org/10.3390/jcm10030544
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. https://doi.org/10.3390/jcm10030544

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. https://doi.org/10.3390/jcm10030544

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. https://doi.org/10.3390/jcm10030544

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