ArticleJournal of the American College of Emergency Physicians open2021
Lung ultrasound in predicting COVID-19 clinical outcomes: A prospective observational study.
Article in Journal of the American College of Emergency Physicians open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 18 citations in OpenAlex.
- Article
- Artificial intelligence in respiratory care.Frontiers in digital health · 2024Review
- Using Iterative RE-AIM to enhance hospitalist adoption of lung ultrasound in the management of patients with COVID-19: an implementation pilot study.Implementation science communications · 2022Article
- Point-of-Care Lung Ultrasound Predicts Severe Disease and Death Due to COVID-19: A Prospective Cohort Study.Critical care explorations · 2022Article
- Lung Ultrasound Characteristics in Neonates With Positive Real Time Polymerase Chain Reaction for SARS-CoV-2 on a Tertiary Level Referral Hospital in Mexico City.Frontiers in pediatrics · 2022Article
- Lung ultrasound in predicting COVID-19 clinical outcomes: A prospective observational study.Journal of the American College of Emergency Physicians open · 2021Article
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Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
STUDY
objectiveWe sought to determine the ability of lung point-of-care ultrasound (POCUS) to predict mechanical ventilation and in-hospital mortality in patients with coronavirus disease 2019 (COVID-19).
methodsThis was a prospective observational study of a convenience sample of patients with confirmed COVID-19 presenting to 2 tertiary hospital emergency departments (EDs) in Iran between March and April 2020. An emergency physician attending sonographer performed a 12-zone bilateral lung ultrasound in all patients. Research associates followed the patients on their clinical course. We determined the frequency of positive POCUS findings, the geographic distribution of lung involvement, and lung severity scores. We used multivariable logistic regression to associate lung POCUS findings with clinical outcomes.
resultsA total of 125 patients with COVID-like symptoms were included, including 109 with confirmed COVID-19. Among the included patients, 33 (30.3%) patients were intubated, and in-hospital mortality was reported in 19 (17.4%). Lung POCUS findings included pleural thickening 95.4%, B-lines 90.8%, subpleural consolidation 86.2%, consolidation 46.8%, effusions 19.3%, and atelectasis 18.3%. Multivariable logistic regression incorporating binary and scored POCUS findings were able to identify those at highest risk for need of mechanical ventilation (area under the curve 0.80) and in-hospital mortality (area under the curve 0.87). In the binary model ultrasound (US) findings in the anterior lung fields were significantly associated with a need for intubation and mechanical ventilation (odds ratio [OR] 3.67; 0.62-21.6). There was an inverse relationship between mortality and posterior lung field involvement (OR 0.05; 0.01-0.23; and scored OR of 0.57; 0.40-0.82). Anterior lung field involvement was not associated with mortality.
conclusionsIn patients with COVID-19, the anatomic distribution of findings on lung ultrasound is associated with outcomes. Lung POCUS-based models may help clinicians to identify those patients with COVID-19 at risk for clinical deterioration.Key Words: COVID-19; Lung Ultrasound; Mechanical ventilation; Prediction; ICU admission; Mortality; Clinical outcome; Risk stratification; Diagnostic accuracy.
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