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Latent class analysis of imaging and clinical respiratory parameters from patients with COVID-19-related ARDS identifies recruitment subphenotypes.
Filippini, Daan F L; Di Gennaro, Elisa; van Amstel, Rombout B E; Beenen, Ludo F M; Grasso, Salvatore; Pisani, Luigi; Bos, Lieuwe D J; Smit, Marry R.
  • Filippini DFL; Department of Intensive Care Medicine, Amsterdam UMC, University of Amsterdam, 1105AZ, Amsterdam, The Netherlands. d.filippini@amsterdamumc.nl.
  • Di Gennaro E; Department of Intensive Care Medicine, Amsterdam UMC, University of Amsterdam, 1105AZ, Amsterdam, The Netherlands.
  • van Amstel RBE; Faculty of Medicine, University of Bari, Bari, Italy.
  • Beenen LFM; Department of Intensive Care Medicine, Amsterdam UMC, University of Amsterdam, 1105AZ, Amsterdam, The Netherlands.
  • Grasso S; Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
  • Pisani L; Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy.
  • Bos LDJ; Critical Care Africa Asia Network, Mahidol Oxford Research Unit, Bangkok, Thailand.
  • Smit MR; Department of Anesthesia and Intensive Care, Miulli Regional Hospital, Acquiviva Delle Fonti, Bari, Italy.
Crit Care ; 26(1): 363, 2022 11 25.
Article in English | MEDLINE | ID: covidwho-2139382
ABSTRACT

BACKGROUND:

Patients with COVID-19-related acute respiratory distress syndrome (ARDS) require respiratory support with invasive mechanical ventilation and show varying responses to recruitment manoeuvres. In patients with ARDS not related to COVID-19, two pulmonary subphenotypes that differed in recruitability were identified using latent class analysis (LCA) of imaging and clinical respiratory parameters. We aimed to evaluate if similar subphenotypes are present in patients with COVID-19-related ARDS.

METHODS:

This is the retrospective analysis of mechanically ventilated patients with COVID-19-related ARDS who underwent CT scans at positive end-expiratory pressure of 10 cmH2O and after a recruitment manoeuvre at 20 cmH2O. LCA was applied to quantitative CT-derived parameters, clinical respiratory parameters, blood gas analysis and routine laboratory values before recruitment to identify subphenotypes.

RESULTS:

99 patients were included. Using 12 variables, a two-class LCA model was identified as best fitting. Subphenotype 2 (recruitable) was characterized by a lower PaO2/FiO2, lower normally aerated lung volume and lower compliance as opposed to a higher non-aerated lung mass and higher mechanical power when compared to subphenotype 1 (non-recruitable). Patients with subphenotype 2 had more decrease in non-aerated lung mass in response to a standardized recruitment manoeuvre (p = 0.024) and were mechanically ventilated longer until successful extubation (adjusted SHR 0.46, 95% CI 0.23-0.91, p = 0.026), while no difference in survival was found (p = 0.814).

CONCLUSIONS:

A recruitable and non-recruitable subphenotype were identified in patients with COVID-19-related ARDS. These findings are in line with previous studies in non-COVID-19-related ARDS and suggest that a combination of imaging and clinical respiratory parameters could facilitate the identification of recruitable lungs before the manoeuvre.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Respiratory Distress Syndrome / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: Crit Care Year: 2022 Document Type: Article Affiliation country: S13054-022-04251-2

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Respiratory Distress Syndrome / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: Crit Care Year: 2022 Document Type: Article Affiliation country: S13054-022-04251-2