RESUMEN
BACKGROUND: Automated analysis of lung computed tomography (CT) scans may help characterize subphenotypes of acute respiratory illness. We integrated lung CT features measured via deep learning with clinical and laboratory data in spontaneously breathing subjects to enhance the identification of COVID-19 subphenotypes. METHODS: This is a multicenter observational cohort study in spontaneously breathing patients with COVID-19 respiratory failure exposed to early lung CT within 7 days of admission. We explored lung CT images using deep learning approaches to quantitative and qualitative analyses; latent class analysis (LCA) by using clinical, laboratory and lung CT variables; regional differences between subphenotypes following 3D spatial trajectories. RESULTS: Complete datasets were available in 559 patients. LCA identified two subphenotypes (subphenotype 1 and 2). As compared with subphenotype 2 (n = 403), subphenotype 1 patients (n = 156) were older, had higher inflammatory biomarkers, and were more hypoxemic. Lungs in subphenotype 1 had a higher density gravitational gradient with a greater proportion of consolidated lungs as compared with subphenotype 2. In contrast, subphenotype 2 had a higher density submantellar-hilar gradient with a greater proportion of ground glass opacities as compared with subphenotype 1. Subphenotype 1 showed higher prevalence of comorbidities associated with endothelial dysfunction and higher 90-day mortality than subphenotype 2, even after adjustment for clinically meaningful variables. CONCLUSIONS: Integrating lung-CT data in a LCA allowed us to identify two subphenotypes of COVID-19, with different clinical trajectories. These exploratory findings suggest a role of automated imaging characterization guided by machine learning in subphenotyping patients with respiratory failure. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04395482. Registration date: 19/05/2020.
Asunto(s)
COVID-19 , Pulmón , Fenotipo , Insuficiencia Respiratoria , Tomografía Computarizada por Rayos X , Humanos , COVID-19/diagnóstico por imagen , COVID-19/fisiopatología , Tomografía Computarizada por Rayos X/métodos , Femenino , Masculino , Persona de Mediana Edad , Pulmón/diagnóstico por imagen , Pulmón/fisiopatología , Anciano , Insuficiencia Respiratoria/diagnóstico por imagen , Insuficiencia Respiratoria/etiología , Insuficiencia Respiratoria/fisiopatología , Estudios de Cohortes , AdultoRESUMEN
Barotrauma occurs in a significant number of patients with COVID-19 interstitial pneumonia undergoing mechanical ventilation. The aim of the current study was to investigate whether the Brixia score (BS) calculated on chest-X-rays acquired at the Emergency Room was associated with barotrauma. We retrospectively evaluated 117 SARS-CoV-2 patients presented to the Emergency Department (ED) and then admitted to the intensive care unit (ICU) for mechanical ventilation between February and April 2020. Subjects were divided into two groups according to the occurrence of barotrauma during their hospitalization. CXRs performed at ED admittance were assessed using the Brixia score. Distribution of barotrauma (pneumomediastinum, pneumothorax, subcutaneous emphysema) was identified in chest CT scans. Thirty-eight subjects (32.5%) developed barotrauma (25 pneumomediastinum, 24 pneumothorax, 24 subcutaneous emphysema). In the barotrauma group we observed higher Brixia score values compared to the non-barotrauma group (mean value 12.18 vs. 9.28), and logistic regression analysis confirmed that Brixia score is associated with the risk of barotrauma. In this work, we also evaluated the relationship between barotrauma and clinical and ventilatory parameters: SOFA score calculated at ICU admittance and number of days of non-invasive ventilation (NIV) prior to intubation emerged as other potential predictors of barotrauma.
Asunto(s)
Barotrauma , COVID-19 , Enfisema Mediastínico , Neumotórax , Enfisema Subcutáneo , Humanos , Respiración Artificial/efectos adversos , Neumotórax/diagnóstico por imagen , Neumotórax/epidemiología , Neumotórax/etiología , Estudios Retrospectivos , Enfisema Mediastínico/diagnóstico por imagen , Enfisema Mediastínico/epidemiología , Enfisema Mediastínico/etiología , Pandemias , Rayos X , COVID-19/diagnóstico por imagen , Barotrauma/diagnóstico por imagen , Barotrauma/epidemiología , Barotrauma/etiología , Enfisema Subcutáneo/diagnóstico por imagen , Enfisema Subcutáneo/epidemiología , Enfisema Subcutáneo/etiología , Hospitalización , Italia/epidemiologíaRESUMEN
A 21-year-old patient has been treated in emergency with venovenous extracorporeal membrane oxygenation after severe thoracic trauma causing severe air leak and haemothorax. The extracorporeal assistance was managed without heparin for 10 days till the full recovery of the lung, and no side-effect was recorded.