Point-of-Care Lung Ultrasound Predicts Severe Disease and Death Due to COVID-19: A Prospective Cohort Study

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Abstract

The clinical utility of point-of-care lung ultrasound (LUS) among hospitalized patients with COVID-19 is unclear.

DESIGN:

Prospective cohort study.

SETTING:

A large tertiary care center in Maryland, between April 2020 and September 2021.

PATIENTS:

Hospitalized adults (≥ 18 yr old) with positive severe acute respiratory syndrome coronavirus 2 reverse transcriptase-polymerase chain reaction results.

INTERVENTIONS:

None.

MEASUREMENTS AND MAIN RESULTS:

All patients were scanned using a standardized protocol including 12 lung zones and followed to determine clinical outcomes until hospital discharge and vital status at 28 days. Ultrasounds were independently reviewed for lung and pleural line artifacts and abnormalities, and the mean LUS Score (mLUSS) (ranging from 0 to 3) across lung zones was determined. The primary outcome was time to ICU-level care, defined as high-flow oxygen, noninvasive, or invasive mechanical ventilation, within 28 days of the initial ultrasound. Cox proportional hazards regression models adjusted for age and sex were fit for mLUSS and each ultrasound covariate. A total of 264 participants were enrolled in the study; the median age was 61 years and 114 participants (43.2%) were female. The median mLUSS was 1.0 (interquartile range, 0.5–1.3). Following enrollment, 27 participants (10.0%) went on to require ICU-level care, and 14 (5.3%) subsequently died by 28 days. Each increase in mLUSS at enrollment was associated with disease progression to ICU-level care (adjusted hazard ratio [aHR], 3.61; 95% CI, 1.27–10.2) and 28-day mortality (aHR, 3.10; 95% CI, 1.29–7.50). Pleural line abnormalities were independently associated with disease progression to death (aHR, 20.93; CI, 3.33–131.30).

CONCLUSIONS:

Participants with a mLUSS greater than or equal to 1 or pleural line changes on LUS had an increased likelihood of subsequent requirement of high-flow oxygen or greater. LUS is a promising tool for assessing risk of COVID-19 progression at the bedside.

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  1. SciScore for 10.1101/2021.12.30.21268558: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: We enrolled adults (≥18 years of age) who tested positive for SARS-CoV-2 on RT-PCR and were admitted to Johns Hopkins Hospital in Baltimore, Maryland into a larger COVID-19 prospective cohort after verbal informed consent, between April 2020 to September 2021 as a convenience sample.
    IRB: This protocol was approved by the Johns Hopkins University Institutional Review Board (IRB00245545).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were analyzed in R (v4.0.2) and Stata, version 16.0 (StataCorp LLC, College Station, TX, USA).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    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:
    There were limitations to the present study. First, not all participants were enrolled prior to admission, and as this was a hospital-based protocol, generally had a minimum requirement of oxygen. Patients were not always enrolled on the day of admission which may have diminished the effect size of differences in POCUS findings. Additionally, those hospitalized with incidental asymptomatic SARS-CoV-2 infection may be less comparable to those with moderate severity, but a sensitivity analysis was performed and inference about risk was unchanged. These factors led to sample size limitations in some of the survival analyses leading to wide confidence intervals, but the qualitative inference was consistent across outcomes and remains important. Further work is ongoing in ambulatory settings and additional sites with standardized follow-up to improve our understanding of the external validity and diagnostic accuracy among additional populations including non-hospitalized individuals with COVID 19. Lastly, while the mLUSS provide valuable prognostic information, additional lung ultrasound features such as consolidations or pleural line changes appear to be useful prognostic findings and should be evaluated for incorporation into models with subsequent validation. Future research with machine learning and unsupervised approaches can help optimize LUS for clinical use.

    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.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

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