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Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study
PURPOSE: To analyze the application of a lung ultrasound (LUS)-based diagnostic approach to patients suspected of COVID-19, combining the LUS likelihood of COVID-19 pneumonia with patient’s symptoms and clinical history. METHODS: This is an international multicenter observational study in 20 US and...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980130/ https://www.ncbi.nlm.nih.gov/pubmed/33743018 http://dx.doi.org/10.1007/s00134-021-06373-7 |
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author | Volpicelli, Giovanni Gargani, Luna Perlini, Stefano Spinelli, Stefano Barbieri, Greta Lanotte, Antonella Casasola, Gonzalo García Nogué-Bou, Ramon Lamorte, Alessandro Agricola, Eustachio Villén, Tomas Deol, Paramjeet Singh Nazerian, Peiman Corradi, Francesco Stefanone, Valerio Fraga, Denise Nicole Navalesi, Paolo Ferre, Robinson Boero, Enrico Martinelli, Giampaolo Cristoni, Lorenzo Perani, Cristiano Vetrugno, Luigi McDermott, Cian Miralles-Aguiar, Francisco Secco, Gianmarco Zattera, Caterina Salinaro, Francesco Grignaschi, Alice Boccatonda, Andrea Giostra, Fabrizio Infante, Marta Nogué Covella, Michele Ingallina, Giacomo Burkert, Julia Frumento, Paolo Forfori, Francesco Ghiadoni, Lorenzo |
author_facet | Volpicelli, Giovanni Gargani, Luna Perlini, Stefano Spinelli, Stefano Barbieri, Greta Lanotte, Antonella Casasola, Gonzalo García Nogué-Bou, Ramon Lamorte, Alessandro Agricola, Eustachio Villén, Tomas Deol, Paramjeet Singh Nazerian, Peiman Corradi, Francesco Stefanone, Valerio Fraga, Denise Nicole Navalesi, Paolo Ferre, Robinson Boero, Enrico Martinelli, Giampaolo Cristoni, Lorenzo Perani, Cristiano Vetrugno, Luigi McDermott, Cian Miralles-Aguiar, Francisco Secco, Gianmarco Zattera, Caterina Salinaro, Francesco Grignaschi, Alice Boccatonda, Andrea Giostra, Fabrizio Infante, Marta Nogué Covella, Michele Ingallina, Giacomo Burkert, Julia Frumento, Paolo Forfori, Francesco Ghiadoni, Lorenzo |
author_sort | Volpicelli, Giovanni |
collection | PubMed |
description | PURPOSE: To analyze the application of a lung ultrasound (LUS)-based diagnostic approach to patients suspected of COVID-19, combining the LUS likelihood of COVID-19 pneumonia with patient’s symptoms and clinical history. METHODS: This is an international multicenter observational study in 20 US and European hospitals. Patients suspected of COVID-19 were tested with reverse transcription-polymerase chain reaction (RT-PCR) swab test and had an LUS examination. We identified three clinical phenotypes based on pre-existing chronic diseases (mixed phenotype), and on the presence (severe phenotype) or absence (mild phenotype) of signs and/or symptoms of respiratory failure at presentation. We defined the LUS likelihood of COVID-19 pneumonia according to four different patterns: high (HighLUS), intermediate (IntLUS), alternative (AltLUS), and low (LowLUS) probability. The combination of patterns and phenotypes with RT-PCR results was described and analyzed. RESULTS: We studied 1462 patients, classified in mild (n = 400), severe (n = 727), and mixed (n = 335) phenotypes. HighLUS and IntLUS showed an overall sensitivity of 90.2% (95% CI 88.23–91.97%) in identifying patients with positive RT-PCR, with higher values in the mixed (94.7%) and severe phenotype (97.1%), and even higher in those patients with objective respiratory failure (99.3%). The HighLUS showed a specificity of 88.8% (CI 85.55–91.65%) that was higher in the mild phenotype (94.4%; CI 90.0–97.0%). At multivariate analysis, the HighLUS was a strong independent predictor of RT-PCR positivity (odds ratio 4.2, confidence interval 2.6–6.7, p < 0.0001). CONCLUSION: Combining LUS patterns of probability with clinical phenotypes at presentation can rapidly identify those patients with or without COVID-19 pneumonia at bedside. This approach could support and expedite patients’ management during a pandemic surge. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00134-021-06373-7. |
format | Online Article Text |
id | pubmed-7980130 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-79801302021-03-23 Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study Volpicelli, Giovanni Gargani, Luna Perlini, Stefano Spinelli, Stefano Barbieri, Greta Lanotte, Antonella Casasola, Gonzalo García Nogué-Bou, Ramon Lamorte, Alessandro Agricola, Eustachio Villén, Tomas Deol, Paramjeet Singh Nazerian, Peiman Corradi, Francesco Stefanone, Valerio Fraga, Denise Nicole Navalesi, Paolo Ferre, Robinson Boero, Enrico Martinelli, Giampaolo Cristoni, Lorenzo Perani, Cristiano Vetrugno, Luigi McDermott, Cian Miralles-Aguiar, Francisco Secco, Gianmarco Zattera, Caterina Salinaro, Francesco Grignaschi, Alice Boccatonda, Andrea Giostra, Fabrizio Infante, Marta Nogué Covella, Michele Ingallina, Giacomo Burkert, Julia Frumento, Paolo Forfori, Francesco Ghiadoni, Lorenzo Intensive Care Med Original PURPOSE: To analyze the application of a lung ultrasound (LUS)-based diagnostic approach to patients suspected of COVID-19, combining the LUS likelihood of COVID-19 pneumonia with patient’s symptoms and clinical history. METHODS: This is an international multicenter observational study in 20 US and European hospitals. Patients suspected of COVID-19 were tested with reverse transcription-polymerase chain reaction (RT-PCR) swab test and had an LUS examination. We identified three clinical phenotypes based on pre-existing chronic diseases (mixed phenotype), and on the presence (severe phenotype) or absence (mild phenotype) of signs and/or symptoms of respiratory failure at presentation. We defined the LUS likelihood of COVID-19 pneumonia according to four different patterns: high (HighLUS), intermediate (IntLUS), alternative (AltLUS), and low (LowLUS) probability. The combination of patterns and phenotypes with RT-PCR results was described and analyzed. RESULTS: We studied 1462 patients, classified in mild (n = 400), severe (n = 727), and mixed (n = 335) phenotypes. HighLUS and IntLUS showed an overall sensitivity of 90.2% (95% CI 88.23–91.97%) in identifying patients with positive RT-PCR, with higher values in the mixed (94.7%) and severe phenotype (97.1%), and even higher in those patients with objective respiratory failure (99.3%). The HighLUS showed a specificity of 88.8% (CI 85.55–91.65%) that was higher in the mild phenotype (94.4%; CI 90.0–97.0%). At multivariate analysis, the HighLUS was a strong independent predictor of RT-PCR positivity (odds ratio 4.2, confidence interval 2.6–6.7, p < 0.0001). CONCLUSION: Combining LUS patterns of probability with clinical phenotypes at presentation can rapidly identify those patients with or without COVID-19 pneumonia at bedside. This approach could support and expedite patients’ management during a pandemic surge. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00134-021-06373-7. Springer Berlin Heidelberg 2021-03-20 2021 /pmc/articles/PMC7980130/ /pubmed/33743018 http://dx.doi.org/10.1007/s00134-021-06373-7 Text en © Springer-Verlag GmbH Germany, part of Springer Nature 2021, corrected publication 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Volpicelli, Giovanni Gargani, Luna Perlini, Stefano Spinelli, Stefano Barbieri, Greta Lanotte, Antonella Casasola, Gonzalo García Nogué-Bou, Ramon Lamorte, Alessandro Agricola, Eustachio Villén, Tomas Deol, Paramjeet Singh Nazerian, Peiman Corradi, Francesco Stefanone, Valerio Fraga, Denise Nicole Navalesi, Paolo Ferre, Robinson Boero, Enrico Martinelli, Giampaolo Cristoni, Lorenzo Perani, Cristiano Vetrugno, Luigi McDermott, Cian Miralles-Aguiar, Francisco Secco, Gianmarco Zattera, Caterina Salinaro, Francesco Grignaschi, Alice Boccatonda, Andrea Giostra, Fabrizio Infante, Marta Nogué Covella, Michele Ingallina, Giacomo Burkert, Julia Frumento, Paolo Forfori, Francesco Ghiadoni, Lorenzo Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study |
title | Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study |
title_full | Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study |
title_fullStr | Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study |
title_full_unstemmed | Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study |
title_short | Lung ultrasound for the early diagnosis of COVID-19 pneumonia: an international multicenter study |
title_sort | lung ultrasound for the early diagnosis of covid-19 pneumonia: an international multicenter study |
topic | Original |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980130/ https://www.ncbi.nlm.nih.gov/pubmed/33743018 http://dx.doi.org/10.1007/s00134-021-06373-7 |
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