Prognostic factors of worse outcome for hospitalized COVID-19 patients, with emphasis on chest computed tomography data: a retrospective study

ABSTRACT Objective: To evaluate anthropometric and clinical data, muscle mass, subcutaneous fat, spine bone mineral density, extent of acute pulmonary disease related to COVID-19, quantification of pulmonary emphysema, coronary calcium, and hepatic steatosis using chest computed tomography of hospitalized patients with confirmed diagnosis of COVID-19 pneumonia and verify its association with disease severity. Methods: A total of 123 adults hospitalized due to COVID-19 pneumonia were enrolled in the present study, which evaluated the anthropometric, clinical and chest computed tomography data (pectoral and paravertebral muscle area and density, subcutaneous fat, thoracic vertebral bodies density, degree of pulmonary involvement by disease, coronary calcium quantification, liver attenuation measurement) and their association with poorer prognosis characterized through a combined outcome of intubation and mechanical ventilation, need of intensive care unit, and death. Results: Age (p=0.013), body mass index (p=0.009), lymphopenia (p=0.034), and degree of pulmonary involvement of COVID-19 pneumonia (p<0.001) were associated with poor prognosis. Extent of pulmonary involvement by COVID-19 pneumonia had an odds ratio of 1,329 for a poor prognosis and a cutoff value of 6.5 for increased risk, with a sensitivity of 64.9% and specificity of 67.1%. Conclusion: The present study found an association of high body mass index, older age, extent of pulmonary involvement by COVID-19, and lymphopenia with severity of COVID-19 pneumonia in hospitalized patients..

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:20

Enthalten in:

Einstein (São Paulo) - 20(2022)

Sprache:

Englisch ; Portugiesisch

Beteiligte Personen:

Adham do Amaral e Castro [VerfasserIn]
Patrícia Yokoo [VerfasserIn]
Eduardo Kaiser Ururahy Nunes Fonseca [VerfasserIn]
Jessyca Couto Otoni [VerfasserIn]
Sarah Lustosa Haiek [VerfasserIn]
Hamilton Shoji [VerfasserIn]
Rodrigo Caruso Chate [VerfasserIn]
Andrea Z Pereira [VerfasserIn]
Marcos Roberto Gomes de Queiroz [VerfasserIn]
Marcelo Costa Batista [VerfasserIn]
Gilberto Szarf [VerfasserIn]

Links:

doi.org [kostenfrei]
doaj.org [kostenfrei]
www.scielo.br [kostenfrei]
www.scielo.br [kostenfrei]
Journal toc [kostenfrei]

Themen:

COVID-19
Coronavirus infections
Medicine
Multidetector computed tomography
Obesity
Pneumonia
Prognosis
R
Tomography
X-ray computed

doi:

10.31744/einstein_journal/2022ao6953

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

DOAJ04210761X