Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia in Critically Ill Patients: A Cluster Analysis According to Baseline Characteristics, Biological Features, and Chest CT Scan on Admission
Rattachement africain : fr. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
BACKGROUND: Inconsistent results from COVID-19 studies raise the issue of patient heterogeneity. OBJECTIVE: The objective of this study was to identify homogeneous subgroups of patients (clusters) using baseline characteristics including inflammatory biomarkers and the extent of lung parenchymal lesions on CT, and to compare their outcomes. DESIGN: Retrospective single-center study. SETTING: Medical ICU of the University Hospital of Clermont-Ferrand, France. PATIENTS: All consecutive adult patients aged greater than or equal to 18 years, admitted between March 20, 2020, and August 31, 2021, for COVID-19 pneumonia. INTERVENTIONS: Characteristics at baseline, during ICU stay, and outcomes at day 60 were recorded. On the chest CT performed at admission the extent of lung parenchyma lesions was established by artificial intelligence software. MEASUREMENTS AND MAIN RESULTS: Clusters were determined by hierarchical clustering on principal components using principal component analysis of admission characteristics including plasma interleukin-6, human histocompatibility leukocyte antigen-DR expression rate on blood monocytes (HLA-DR) monocytic-expression rate (mHLA-DR), and the extent of lung parenchymal lesions. Factors associated with day 60 mortality were investigated by univariate survival analysis. Two hundred seventy patients were included. Four clusters were identified and three were fully described. Cluster 1 (obese patients, with moderate hypoxemia, moderate extent of lung parenchymal lesions, no inflammation, and no down-regulation of mHLA-DR) had a better prognosis at day 60 (hazard ratio [HR] = 0.27 [0.15-0.46], p < 0.01), whereas cluster 2 (older patients with comorbidities, moderate extent of lung parenchyma lesions but significant hypoxemia, inflammation, and down-regulation of mHLA-DR) and cluster 3 (patients with severe parenchymal disease, hypoxemia, inflammatory reaction, and down-regulation of mHLA-DR) had an increased risk of mortality (HR = 2.07 [1.37-3.13], p < 0.01 and HR = 1.52 [1-2.32], p = 0.05, respectively). In multivariate analysis, only clusters 1 and 2 were independently associated with day 60 death. CONCLUSIONS: Three clusters with distinct characteristics and outcomes were identified. Such clusters could facilitate the identification of targeted populations for the next trials.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia in Critically Ill Patients: A Cluster Analysis According to Baseline Characteristics, Biological Features, and Chest CT Scan on Admission
- Date Crossref
- 27/10/2023
- Éditeur
- Ovid Technologies (Wolters Kluwer Health)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Centre Hospitalier Universitaire de Clermont-Ferrand pays non établi dans la noticeÉtablissement de santé
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University of Clermont Auvergne pays non établi dans la noticeUniversité ou école supérieure
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Clermont Université pays non établi dans la noticeUniversité ou école supérieure
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Centre National de la Recherche Scientifique pays non établi dans la noticeOrganisme public
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Institut National de Recherche pour l'Agriculture pays non établi dans la noticeOrganisme public
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Centre de Recherche en Nutrition Humaine d'Auvergne pays non établi dans la noticeStructure de recherche
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CHU Clermont-Ferrand pays non établi dans la noticeÉtablissement de santé
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Université Clermont Auvergne pays non établi dans la noticeUniversité ou école supérieure
Centre Hospitalier Universitaire de Clermont-Ferrand, University of Clermont Auvergne et Clermont Université, avec 5 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.