Evidence map›Paper›PMID 34859905›Full record

ArticleJournal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine2022

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

Libertario Demi, Federico Mento, Antonio Di Sabatino, Anna Fiengo, Umberto Sabatini, Veronica Narvena Macioce, Marco Robol, Francesco Tursi, Carmelo Sofia, Chiara Di Cienzo and 3 more

Abstract read
In one paragraph

Article in Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

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  15. New International Guidelines and Consensus on the Use of Lung Ultrasound.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2023
    Review
  16. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Libertario DemiDepartment of Information Engineering and Computer Science, University of Trento, Trento, Italy.ORCID https://orcid.org/0000-0002-0635-2133
Federico MentoDepartment of Information Engineering and Computer Science, University of Trento, Trento, Italy.ORCID https://orcid.org/0000-0002-6571-7809
Antonio Di SabatinoDepartment of Internal Medicine, IRCCS San Matteo Hospital Foundation, University of Pavia, Pavia, Italy.
Anna FiengoDepartment of Internal Medicine, IRCCS San Matteo Hospital Foundation, University of Pavia, Pavia, Italy.
Umberto SabatiniDepartment of Internal Medicine, IRCCS San Matteo Hospital Foundation, University of Pavia, Pavia, Italy.
Veronica Narvena MacioceUOS Pneumologia di Codogno, Asst Lodi, Lodi, Italy.
Marco RobolDepartment of Information Engineering and Computer Science, University of Trento, Trento, Italy.
Francesco TursiUOS Pneumologia di Codogno, Asst Lodi, Lodi, Italy.
Carmelo SofiaPulmonary Medicine Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Chiara Di CienzoPulmonary Medicine Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Andrea SmargiassiPulmonary Medicine Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.ORCID https://orcid.org/0000-0003-0637-7282
Riccardo InchingoloPulmonary Medicine Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Tiziano PerroneDepartment of Internal Medicine, IRCCS San Matteo Hospital Foundation, University of Pavia, Pavia, Italy.ORCID https://orcid.org/0000-0001-8268-3121

Funding

European Institute of Innovation and Technology project UltraOn, EIT Digital 2020Fondazione Valorizzazione Ricerca Trentina grant 1, COVID-19 2020
6 · The paper itself

Abstract

objectivesWorldwide, 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.

methodsLUS 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.

resultsA 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.

conclusionsA 12-areas acquisition protocol is recommended for both COVID-19 and post-COVID-19 patients, also during follow-up.

Indexed as

COVID-19HumansLongitudinal StudiesLungSARS-CoV-2Ultrasonographyartificial intelligenceCOVID-19lung ultrasoundpost-COVID-19SARS-CoV-2

Identifiers

PMID34859905
PMCPMC9015439

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.