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Carvalho, Carlos Roberto Ribeiro
;
Lamas, Celina Almeida
;
Chate, Rodrigo Caruso
;
Salge, Joao Marcos
;
Sawamura, Marcio Valente Yamada
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de Albuquerque, Andre L. P.
;
Toufen Jr, Carlos
;
Lima, Daniel Mario
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Garcia, Michelle Louvaes
;
Scudeller, Paula Gobi
;
Nomura, Cesar Higa
;
Gutierrez, Marco Antonio
;
Baldi, Bruno Guedes
;
HCFMUSP Covid-19 Study Grp
Número total de Autores: 14
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| Tipo de documento: | Artigo Científico |
| Fonte: | PLoS One; v. 18, n. 1, p. 16-pg., 2023-01-20. |
| Resumo | |
BackgroundCoronavirus disease (COVID-19) survivors exhibit multisystemic alterations after hospitalization. Little is known about long-term imaging and pulmonary function of hospitalized patients intensive care unit (ICU) who survive COVID-19. We aimed to investigate long-term consequences of COVID-19 on the respiratory system of patients discharged from hospital ICU and identify risk factors associated with chest computed tomography (CT) lesion severity. MethodsA prospective cohort study of COVID-19 patients admitted to a tertiary hospital ICU in Brazil (March-August/2020), and followed-up six-twelve months after hospital admission. Initial assessment included: modified Medical Research Council dyspnea scale, SpO(2) evaluation, forced vital capacity, and chest X-Ray. Patients with alterations in at least one of these examinations were eligible for CT and pulmonary function tests (PFTs) approximately 16 months after hospital admission. Primary outcome: CT lesion severity (fibrotic-like or non-fibrotic-like). Baseline clinical variables were used to build a machine learning model (ML) to predict the severity of CT lesion. ResultsIn total, 326 patients (72%) were eligible for CT and PFTs. COVID-19 CT lesions were identified in 81.8% of patients, and half of them showed mild restrictive lung impairment and impaired lung diffusion capacity. Patients with COVID-19 CT findings were stratified into two categories of lesion severity: non-fibrotic-like (50.8%-ground-glass opacities/reticulations) and fibrotic-like (49.2%-traction bronchiectasis/architectural distortion). No association between CT feature severity and altered lung diffusion or functional restrictive/obstructive patterns was found. The ML detected that male sex, ICU and invasive mechanic ventilation (IMV) period, tracheostomy and vasoactive drug need during hospitalization were predictors of CT lesion severity(sensitivity,0.78 +/- 0.02;specificity,0.79 +/- 0.01;F1-score,0.78 +/- 0.02;positive predictive rate,0.78 +/- 0.02; accuracy,0.78 +/- 0.02; and area under the curve,0.83 +/- 0.01). ConclusionICU hospitalization due to COVID-19 led to respiratory system alterations six-twelve months after hospital admission. Male sex and critical disease acute phase, characterized by a longer ICU and IMV period, and need for tracheostomy and vasoactive drugs, were risk factors for severe CT lesions six-twelve months after hospital admission. (AU) | |
| Processo FAPESP: | 14/50889-7 - INCT 2014: em Medicina Assistida por Computação Científica (INCT-MACC) |
| Beneficiário: | José Eduardo Krieger |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |
| Processo FAPESP: | 16/17078-0 - Mineração, indexação e visualização de Big Data no contexto de sistemas de apoio à decisão clínica (MIVisBD) |
| Beneficiário: | Agma Juci Machado Traina |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |