Lung injury in patients with or suspected COVID-19 : a comparison between lung ultrasound and chest CT-scanner severity assessments, an observational study

  1. Mehdi Benchoufi
  2. Jerôme Bokobza
  3. Anthony Chauvin
  4. Elisabeth Dion
  5. Marie-Laure Baranne
  6. Fabien Levan
  7. Maxime Gautier
  8. Delphine Cantin
  9. Thomas d’Humières
  10. Cédric Gil-Jardiné
  11. Sylvain Benenati
  12. Mathieu Orbelin
  13. Mikaël Martinez
  14. Nathalie Pierre-Kahn
  15. Abdourahmane Diallo
  16. Eric Vicaut
  17. Pierre Bourrier

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Abstract

Background

Chest CT (CT) is the reference for assessing pulmonary injury in suspected or diagnosed COVID-19 with signs of clinical severity. We explored the role of lung ultrasonography (LU) in quickly assessing lung status in these patients.

Methods

eChoVid is a multicentric study based on routinely collected data, conducted in 3 emergency units of Assistance Publique des Hôpitaux de Paris (APHP); 107 patients were included between March 19, 2020 and April 01, 2020 and underwent LU, a short clinical assessment by 2 emergency physicians blinded to each other’s and a CT. LU consisted of scoring lesions in 8 chest zones from 0 to 3, defining a severity global score (GS) ranging from 0 to 24. CT severity score ranged from 0 to 3 according to the extent of interstitial pneumonia signs. 48 patients underwent LU by both an expert and a newly trained physician.

Findings

The GS showed good performance to predict CT severity assessment of COVID-19 as normal versus pathologic: AUC=0.93, maximal Youden index 1 with 95% sensitivity, and 83% specificity. Similar performance was found for CT assessment as normal or minimal versus moderate or severe (n=90): AUC 0.89, maximal Youden index 7 with 86% sensitivity, and 78% specificity. Good agreement was found for zone scoring assessed by new trainee (30mn theory + 30mn practice) and expert (n=14,14*8 checkpoints), weighted kappa 0.85-1; moderate agreement was found for new trainee (n=48, 30mn theory) and expert, kappa 0.62-0.81.

Interpretation

GS score is a simple tool to assess lung damage severity in patients with suspected or diagnosed COVID-19. Comparing the performance of new trainees and expert physicians opens a path for adoption beyond the scope of experts. LU is a good candidate for patients triage, especially in case of CT availability issues.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.24.20069633: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    BlindingEmergency physician and ultrasound operator were blinded to each other’s findings.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    - Limitations of the study: LU severity score GS may be improved in many ways. First, the score carries information about the severity of lung injuries but does not sufficiently address their extension. For instance, for equal grade 3 scoring, some patients may have only one chest point graded 3 while others may have 3 chest points graded 1. Hence GS does not reflect the disease extension. Scores such as the median, the average or the maximum severity ultrasound grading are not pertinent. They are too naive to include specific or sufficient information on the extension of lung lesions. Besides, let us indicate that we collapsed the CT score “extended”, “severe”, “critical” to “severe” out of clinical simplicity, in order to match the 4 grades ultrasound scoring. In order to improve the ultrasound scoring, a further study is ongoing comparing CT and LU for each chest point, and associated with more refined statistics based on machine learning techniques taking into account linear and non-linearity effects such as the non-linear jump in condition between GS at 0 and 1. Although this approach suggests gains in specificity, a more complex scoring may not be easy to compute in practice. Only 6 CT were normal. Hence, we lack sufficient data to estimate false positive rate. Also, only 10 ultrasound exams had a 0 grading. Hence, we lack sufficient data to estimate negative predictive value. Also, we merged results from patients consulting in EUs of Hospital Cochin and Hospital Laribo...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. ScreenIT

    SciScore for 10.1101/2020.04.24.20069633: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementOutside the submitted work; she is a member of the echOpen association, developing with a global community handheld ultrasound research tools in open source (software and hardware) Ethics committee approval According to french regulatory rules , the study was approved by the ethical committee N°IRB : IORG0009855 (COMITE DE PROTECTION DES PERSONNES DU SUD-OUEST ET OUTRE-MER 4) with N° CPP2020-03-035a / 2020-A00768-31 / 20.03.24.70826 16 BibliographyRandomizationnot detected.BlindingEmergency physician and ultrasound operator were blinded to each other’s findings.Power Analysisnot detected.Sex as a biological variablenot detected.

    Table 2: Resources

    Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, please follow this link.

  3. Version published to 10.1101/2020.04.24.20069633v3 on medRxiv
  4. Version published to 10.1101/2020.04.24.20069633v1 on medRxiv
  5. Version published to 10.1101/2020.04.24.20069633v2 on medRxiv