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Int. j. cardiovasc. sci. (Impr.) ; 33(5): 479-487, Sept.-Oct. 2020. tab, graf
Artigo em Inglês | LILACS | ID: biblio-1134415

RESUMO

Abstract Background Lung ultrasound (LUS) can detect interstitial alveolar changes confined to the subpleural region, like those described in Covid-19. Objetive To evaluate how LUS findings correlate with chest computed tomography (CT) in patients admitted to the emergency department (ED) with suspicion of Covid-19. Methods Cross-sectional study of 20 patients (median age 43 years; interquartile range, 37-63 years; 50% male). All patients underwent LUS and chest CT on the day of ED admission. Each hemithorax was divided into 6 segments with similar landmarks, and equivalent scores (sc) of lesion severity were defined for both methods. The number of affected segments on LUS (LUSseg) was divided into tertiles (0-1, 2-5, and ≥6), and compared with number of affected segments on CT (CTseg), LUSsc, CTsc, and percentage of affected lung parenchyma through visual analysis (CTvis). ANOVA or Kruskal-Wallis test for continuous variables, chi-square test for categorical variables, and receiver operating characteristic (ROC) curve analysis to define optimal cutoff points were performed. P<0.05 was considered statistically significant. Results Median LUSsc, CTsc, CTseg, and CTvis were significantly different between groups. A clear separation between groups was demonstrated; patients with <2 affected segments on LUS were defined as low risk. The ROC curve showed good discriminative power to predict ≥6 affected segments on CT, with an area under the curve (AUC) of 0.97 and 0.98 for >7 LUSsc and >3 LUSseg, respectively. Conclusion LUS findings correlate with chest CT, and can help identify patients with normal lung or minor pulmonary involvement secondary to Covid-19. Int J Cardiovasc Sci. 2020; [online].ahead print, PP.0-0


Assuntos
Humanos , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Tomografia Computadorizada por Raios X/métodos , Ultrassonografia/métodos , Estudos Transversais , Triagem/métodos , Serviço Hospitalar de Emergência , COVID-19/diagnóstico
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