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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.
  • Ursino M; F-CRIN PARTNERS Platform, AP-HP, Université de Paris, Inserm, F-75010 Paris, France.
  • Dupuis C; INSERM, Centre de Recherche des Cordeliers, Sorbonne Université, USPC, Université de Paris, F-75006 Paris, France.
  • Buetti N; Medical Intensive Care Unit, Gabriel Montpied University Hospital, 63000 Clermont-Ferrand, France.
  • de Montmollin E; Inserm U 1137, Université de Paris, Sorbonne Paris Cite, 75870 Paris, France.
  • Bouadma L; Inserm U 1137, Université de Paris, Sorbonne Paris Cite, 75870 Paris, France.
  • Golgran-Toledano D; Inserm U 1137, Université de Paris, Sorbonne Paris Cite, 75870 Paris, France.
  • Ruckly S; APHP, Medical and Infectious Diseases Intensive Care Unit, Bichat-Claude Bernard Hospital, 75018 Paris, France.
  • Neuville M; Inserm U 1137, Université de Paris, Sorbonne Paris Cite, 75870 Paris, France.
  • Cohen Y; APHP, Medical and Infectious Diseases Intensive Care Unit, Bichat-Claude Bernard Hospital, 75018 Paris, France.
  • Mourvillier B; Polyvalent ICU, Groupe Hospitalier Intercommunal Le Raincy Montfermeil, 93370 Montfermeil, France.
  • Souweine B; Inserm U 1137, Université de Paris, Sorbonne Paris Cite, 75870 Paris, France.
  • Gainnier M; ICUREsearch, Statistical Department, 38160 Saint Marcellin, France.
  • Laurent V; Polyvalent ICU, Hôpital Foch, 92150 Suresnes, France.
  • Terzi N; Intensive Care Unit, CHU Avicenne, Groupe Hospitalier Paris Seine Saint-Denis, AP-HP, 93000 Bobigny, France.
  • Shiami S; UFR SMBH, Université Sorbonne Paris Nord, 93000 Bobigny, France.
  • Reignier J; INSERM, U942, F-75010, 75010 Paris, France.
  • Alberti C; Medical Intensive Care Unit, Robert Debré University Hospital, 51100 Reims, France.
  • Timsit JF; Medical Intensive Care Unit, Gabriel Montpied University Hospital, 63000 Clermont-Ferrand, France.
  • On Behalf Of The Outcomerea Study Group; Service de Médecine Intensive Réanimation, La Timone 2 University Hospital, 13385 Marseille, France.
J Clin Med ; 10(3)2021 Feb 02.
Article in English | MEDLINE | ID: covidwho-1060442
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Language: English Year: 2021 Document Type: Article Affiliation country: Jcm10030544

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Language: English Year: 2021 Document Type: Article Affiliation country: Jcm10030544