Usefulness of lung ultrasound in the early identification of severe COVID-19: results from a prospective study.
Med Ultrason
; 24(2): 146-152, 2022 May 25.
Article
in English
| MEDLINE | ID: covidwho-1513177
ABSTRACT
AIM:
There is growing evidence regarding the imaging findings of coronavirus disease 2019 (COVID-19) in lung ultrasound (LUS); however, its role in predicting the prognosis has yet to be explored. The aim of the study was to assess the relationship between lung ultrasound findings with the degree of respiratory failure measured by the PaO2/FiO2 ratio (PaFi) andthe prognosis of these patients need for non-invasive mechanical ventilation (NIMV), admission to the Intensive Care Unit (ICU) and mortality. MATERIAL ANDMETHOD:
Prospective, longitudinal and observational study performed in patients with confirmed COVID-19 underwent a LUS examination and laboratory tests.RESULTS:
A total of 107 patients were enrolled 93.4% with bilateral involvement and 73.83% presented at least one consolidation. A good inverse correlation (Rho Spearman coefficient -0.897) between the ultrasound score and PaFi was obtained. The AUC for identification of patients with more severe respiratory failure, a moderate and severe ARDS, was 0.97 (CI 95% 0.95-1) and a cut-off score of 34.5 showed a sensitivity of 0.94 and a specificity of 0.91. The Kappa index showed a high concordance (0.83) of the classification by ultrasound lunginvolvement and ARDS.CONCLUSIONS:
The combination of the ultrasound score and the presence of respiratory failure can easily identify patients with a higher risk to present complications.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Respiratory Distress Syndrome
/
Respiratory Insufficiency
/
COVID-19
Type of study:
Cohort study
/
Diagnostic study
/
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Med Ultrason
Journal subject:
Diagnostic Imaging
Year:
2022
Document Type:
Article
Affiliation country:
Mu-3263
Similar
MEDLINE
...
LILACS
LIS