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Lung Ultrasound in COVID‐19 and Post‐COVID‐19 Patients, an Evidence‐Based Approach

OBJECTIVES: Worldwide, lung ultrasound (LUS) was utilized to assess coronavirus disease 2019 (COVID‐19) patients. Often, imaging protocols were however defined arbitrarily and not following an evidence‐based approach. Moreover, extensive studies on LUS in post‐COVID‐19 patients are currently lacking...

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Detalles Bibliográficos
Autores principales: Demi, Libertario, Mento, Federico, Di Sabatino, Antonio, Fiengo, Anna, Sabatini, Umberto, Macioce, Veronica Narvena, Robol, Marco, Tursi, Francesco, Sofia, Carmelo, Di Cienzo, Chiara, Smargiassi, Andrea, Inchingolo, Riccardo, Perrone, Tiziano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9015439/
https://www.ncbi.nlm.nih.gov/pubmed/34859905
http://dx.doi.org/10.1002/jum.15902
Descripción
Sumario:OBJECTIVES: Worldwide, lung ultrasound (LUS) was utilized to assess coronavirus disease 2019 (COVID‐19) patients. Often, imaging protocols were however defined arbitrarily and not following an evidence‐based approach. Moreover, extensive studies on LUS in post‐COVID‐19 patients are currently lacking. This study analyses the impact of different LUS imaging protocols on the evaluation of COVID‐19 and post‐COVID‐19 LUS data. METHODS: LUS data from 220 patients were collected, 100 COVID‐19 positive and 120 post‐COVID‐19. A validated and standardized imaging protocol based on 14 scanning areas and a 4‐level scoring system was implemented. We utilized this dataset to compare the capability of 5 imaging protocols, respectively based on 4, 8, 10, 12, and 14 scanning areas, to intercept the most important LUS findings. This to evaluate the optimal trade‐off between a time‐efficient imaging protocol and an accurate LUS examination. We also performed a longitudinal study, aimed at investigating how to eventually simplify the protocol during follow‐up. Additionally, we present results on the agreement between AI models and LUS experts with respect to LUS data evaluation. RESULTS: A 12‐areas protocol emerges as the optimal trade‐off, for both COVID‐19 and post‐COVID‐19 patients. For what concerns follow‐up studies, it appears not to be possible to reduce the number of scanning areas. Finally, COVID‐19 and post‐COVID‐19 LUS data seem to show differences capable to confuse AI models that were not trained on post‐COVID‐19 data, supporting the hypothesis of the existence of LUS patterns specific to post‐COVID‐19 patients. CONCLUSIONS: A 12‐areas acquisition protocol is recommended for both COVID‐19 and post‐COVID‐19 patients, also during follow‐up.