Correspondence
Application and internal validation of lung ultrasound score in COVID-19 setting: The ECOVITA observational study. Authors’ reply
L. Rinaldia,
, F. Perrottab
Corresponding author
luca.rinaldi@unimol.it
Corresponding author at: Department of Medicine and Health Sciences “V. Tiberio”, Università degli Studi del Molise, Via G. Paolo II, 86100 Campobasso, Italy.
Corresponding author at: Department of Medicine and Health Sciences “V. Tiberio”, Università degli Studi del Molise, Via G. Paolo II, 86100 Campobasso, Italy.
Read
550
Timeswas read the article
186
Total PDF
364
Total HTML
Share statistics
array:22 [ "pii" => "S2531043724000977" "issn" => "25310437" "doi" => "10.1016/j.pulmoe.2024.06.004" "estado" => "S200" "fechaPublicacion" => "2024-07-15" "aid" => "1981" "copyright" => "Sociedade Portuguesa de Pneumologia" "copyrightAnyo" => "2024" "documento" => "simple-article" "crossmark" => 0 "subdocumento" => "cor" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "itemSiguiente" => array:17 [ "pii" => "S2531043724000941" "issn" => "25310437" "doi" => "10.1016/j.pulmoe.2024.06.001" "estado" => "S200" "fechaPublicacion" => "2024-07-15" "aid" => "1978" "copyright" => "Sociedade Portuguesa de Pneumologia" "documento" => "simple-article" "crossmark" => 0 "subdocumento" => "cor" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "en" => array:8 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Correspondence</span>" "titulo" => "Application and internal validation of lung ultrasound score in COVID-19 setting: Correspondence" "tienePdf" => "en" "tieneTextoCompleto" => "en" "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "H. Daungsupawong, V. Wiwanitkit" "autores" => array:2 [ 0 => array:2 [ "nombre" => "H." "apellidos" => "Daungsupawong" ] 1 => array:2 [ "nombre" => "V." "apellidos" => "Wiwanitkit" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2531043724000941?idApp=UINPBA00004E" "url" => "/25310437/unassign/S2531043724000941/v1_202407150419/en/main.assets" ] "itemAnterior" => array:18 [ "pii" => "S2531043720300842" "issn" => "25310437" "doi" => "10.1016/j.pulmoe.2020.04.001" "estado" => "S200" "fechaPublicacion" => "2020-04-26" "aid" => "1458" "copyright" => "Sociedade Portuguesa de Pneumologia" "documento" => "simple-article" "crossmark" => 0 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "dup" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "en" => array:8 [ "idiomaDefecto" => true "titulo" => "WITHDRAWN: Covid-19: Round and oval areas of ground-glass opacity" "tienePdf" => "en" "tieneTextoCompleto" => 0 "tieneResumen" => "en" "contieneResumen" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "W. Schmitt, E. Marchiori" "autores" => array:2 [ 0 => array:2 [ "nombre" => "W." "apellidos" => "Schmitt" ] 1 => array:2 [ "nombre" => "E." "apellidos" => "Marchiori" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2531043720300842?idApp=UINPBA00004E" "url" => "/25310437/unassign/S2531043720300842/v2_202103160709/en/main.assets" ] "en" => array:11 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Correspondence</span>" "titulo" => "Application and internal validation of lung ultrasound score in COVID-19 setting: The ECOVITA observational study. Authors’ reply" "tieneTextoCompleto" => true "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "L. Rinaldi, F. Perrotta" "autores" => array:2 [ 0 => array:4 [ "nombre" => "L." "apellidos" => "Rinaldi" "email" => array:1 [ 0 => "luca.rinaldi@unimol.it" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0001" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0001" ] ] ] 1 => array:3 [ "nombre" => "F." "apellidos" => "Perrotta" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0002" ] ] ] ] "afiliaciones" => array:2 [ 0 => array:3 [ "entidad" => "Department of Medicine and Health Sciences “V. Tiberio”, Università degli Studi del Molise, Campobasso, Italy" "etiqueta" => "a" "identificador" => "aff0001" ] 1 => array:3 [ "entidad" => "Department of Translational Medical Sciences, University of Campania L. Vanvitelli, "Monaldi" Hospital, Naples, Italy" "etiqueta" => "b" "identificador" => "aff0002" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0001" "etiqueta" => "⁎" "correspondencia" => "Corresponding author at: Department of Medicine and Health Sciences “V. Tiberio”, Università degli Studi del Molise, Via G. Paolo II, 86100 Campobasso, Italy." ] ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><p id="para0001" class="elsevierStylePara elsevierViewall">We thank Dr. Daungsupawong and Dr. Wiwanitkit for their important comments<a class="elsevierStyleCrossRef" href="#bib0001"><span class="elsevierStyleSup">1</span></a> related to our study.<a class="elsevierStyleCrossRef" href="#bib0002"><span class="elsevierStyleSup">2</span></a> We agree that inter-operator agreement is crucial in evaluating the results of the presented study, which tests the application of lung ultrasound (LUS) in robust multicenter pragmatic research. In a previous paper, Lerchbaumer et al. documented moderate concordance (κ = 0.41) in inter-observer agreement for the overall LUS score in a small cohort of COVID-19 patients. Interestingly, there was a significant discrepancy for score 1, while higher coefficients for inter- and intra-operator concordance were reported for the other LUS scores (2 and 3), as well as for subpleural consolidations and air bronchograms.<a class="elsevierStyleCrossRef" href="#bib0003"><span class="elsevierStyleSup">3</span></a></p><p id="para0002" class="elsevierStylePara elsevierViewall">Therefore, the generalizability of the results inevitably reflects the quality of the LUS assessment. Consequently, we included only expert clinicians trained according to the recommendations of the Italian Society of Ultrasonography in Medicine and Biology. Additionally, doubtful LUS clips were collected and collegially debated, as reported in our manuscript. We also recognize that various LUS protocols have been widely reported, which limits the interpretation of published data. In our study, we selected a 12-field protocol, which has been shown to be an adequate trade-off in a previous paper including COVID-19 and post-COVID-19 patients.<a class="elsevierStyleCrossRef" href="#bib0004"><span class="elsevierStyleSup">4</span></a> This protocol was used to validate the previous results with robust statistical methods in pragmatic multicenter research, ultimately offering proof of concept for the LUS data validation. These data also documented that the baseline LUS score is an easy and reproducible tool independently associated with adverse outcomes after adjusting for clinical and laboratory parameters. This suggests that, despite COVID-19 pneumonia exhibiting different clinical and radiological phenotypes, LUS evaluation could potentially allow prognostic quantification for COVID-19 patients.</p><p id="para0003" class="elsevierStylePara elsevierViewall">However, these findings should not limit future developments requiring integrated systems, including artificial intelligence (AI) to handle broad data sets. A previous study using a machine learning algorithm documented that urea, lymphocytes, glucose, basophils, and age are predictors of poor survival among COVID-19 patients.<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">5</span></a> Similarly, AI-based imaging interpretation has shown significant potential for LUS evaluation in identifying LUS signs and artifacts (B-lines, airspace consolidations, pleural effusion), evaluating the LUS score, grading COVID-19 severity, and differentiating COVID-19 from other infectious or non-infectious disorders.<a class="elsevierStyleCrossRef" href="#bib0006"><span class="elsevierStyleSup">6</span></a> Despite these potential advantages, the quality of data collection for machine learning also depends on the standardization of LUS. In this context, novel scenarios involving robotic ultrasound combined with data cloud storage systems could enhance the quality of assessment and AI interpretation through the accumulation of large, high-quality datasets essential for AI-based LUS evaluation. Nevertheless, deep learning algorithms have not yet achieved consistency in clinical research. Data interpretability and medical-legal implications present barriers to the widespread use of AI in clinical practice, limiting the translational effects of the current scientific literature.<a class="elsevierStyleCrossRef" href="#bib0007"><span class="elsevierStyleSup">7</span></a></p></span>" "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2024-06-01" "fechaAceptado" => "2024-06-10" "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "cebibsec1" "bibliografiaReferencia" => array:7 [ 0 => array:3 [ "identificador" => "bib0001" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:1 [ "referenciaCompleta" => "Daungsupawong H., Wiwanitkit V. Application and internal validation of lung ultrasound score in COVID-19 setting: correspondence. [PULMOE-D-24-00348]." ] ] ] 1 => array:3 [ "identificador" => "bib0002" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Application and internal validation of lung ultrasound score in COVID-19 setting: the ECOVITA observational study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "L. Rinaldi" 1 => "M. Lugarà" 2 => "V. Simeon" 3 => "F. Perrotta" 4 => "C. Romano" 5 => "C. Iadevaia" ] ] ] ] ] "host" => array:2 [ 0 => array:1 [ "Revista" => array:2 [ "tituloSerie" => "Pulmonology" "fecha" => "2024" ] ] 1 => array:1 [ "WWW" => array:1 [ "link" => "https://doi.org/10.1016/j.pulmoe.2024.04.012" ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0003" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Point-of-care lung ultrasound in COVID-19 patients: inter- and intra-observer agreement in a prospective observational study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M.H. Lerchbaumer" 1 => "J.H. Lauryn" 2 => "U. Bachmann" 3 => "P. Enghard" 4 => "T. Fischer" 5 => "J. Grune" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1038/s41598-021-90153-2" "Revista" => array:6 [ "tituloSerie" => "Sci Rep" "fecha" => "2021" "volumen" => "11" "numero" => "1" "paginaInicial" => "10678" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/34021219" "web" => "Medline" ] ] ] ] ] ] ] ] 3 => array:3 [ "identificador" => "bib0004" "etiqueta" => "4" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Lung ultrasound in COVID-19 and post-COVID-19 patients, an evidence-based approach" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "L. Demi" 1 => "F. Mento" 2 => "A. Di Sabatino" 3 => "A. Fiengo" 4 => "U. Sabatini" 5 => "V. Macioce Narvena" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1002/jum.15902" "Revista" => array:7 [ "tituloSerie" => "J Ultrasound Med" "fecha" => "2022" "volumen" => "41" "numero" => "9" "paginaInicial" => "2203" "paginaFinal" => "2215" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/34859905" "web" => "Medline" ] ] ] ] ] ] ] ] 4 => array:3 [ "identificador" => "bib0005" "etiqueta" => "5" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Algorithms for predicting COVID outcome using ready-to-use laboratorial and clinical data" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A.A. Lourenço" 1 => "P.H.R. Amaral" 2 => "A.A.O. Paim" 3 => "G.F. Marques" 4 => "L. Gomes-de-Pontes" 5 => "C.P.S.M. da Mata" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3389/fpubh.2024.1347334" "Revista" => array:3 [ "tituloSerie" => "Front Public Health" "fecha" => "2024" "volumen" => "12" ] ] ] ] ] ] 5 => array:3 [ "identificador" => "bib0006" "etiqueta" => "6" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Review of machine learning in lung ultrasound in COVID-19 pandemic" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J. Wang" 1 => "X. Yang" 2 => "B. Zhou" 3 => "J.J. Sohn" 4 => "J. Zhou" 5 => "J.T. Jacob" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3390/jimaging8030065" "Revista" => array:6 [ "tituloSerie" => "J Imaging" "fecha" => "2022" "volumen" => "8" "numero" => "3" "paginaInicial" => "65" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/35324620" "web" => "Medline" ] ] ] ] ] ] ] ] 6 => array:3 [ "identificador" => "bib0007" "etiqueta" => "7" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Artificial intelligence (AI) and lung ultrasound in infectious pulmonary disease" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "G. Trovato" 1 => "M. Russo" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.3389/fmed.2021.706794" "Revista" => array:6 [ "tituloSerie" => "Front Med" "fecha" => "2021" "volumen" => "8" "paginaInicial" => "1" "paginaFinal" => "5" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/24402693" "web" => "Medline" ] ] ] ] ] ] ] ] ] ] ] ] ] "idiomaDefecto" => "en" "url" => "/25310437/unassign/S2531043724000977/v1_202407150419/en/main.assets" "Apartado" => null "PDF" => "https://static.elsevier.es/multimedia/25310437/unassign/S2531043724000977/v1_202407150419/en/main.pdf?idApp=UINPBA00004E&text.app=https://journalpulmonology.org/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2531043724000977?idApp=UINPBA00004E" ]
| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 10 | 8 | 18 |
| 2024 October | 50 | 34 | 84 |
| 2024 September | 59 | 33 | 92 |
| 2024 August | 98 | 40 | 138 |
| 2024 July | 147 | 71 | 218 |
