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Lung Ultrasound Findings in Patients With COVID-19 in a UK ED

C

Chelsea and Westminster NHS Foundation Trust

Status

Completed

Conditions

Corona Virus Infection
SARS-CoV Infection
Covid19
Coronavirus

Study type

Observational

Funder types

Other

Identifiers

NCT05065827
C&W20/050
IRAS number 286642 (Other Identifier)

Details and patient eligibility

About

The investigators aim to carry out a retrospective observational study, analysing lung ultrasound images from patients who have presented to A&E for routine diagnostic purposes (ruling out cardiogenic pulmonary oedema, Pulmonary embolism and pericardial effusions) and systematically assessing for abnormalities typical for COVID-19 infection (Pleural irregularities, B lines, consolidations, pleural effusions). Doing this, the investigators will also develop a suggestion for a standardised technique for lung ultrasound which can be transferred to other clinical settings (Intensive Care, Acute medical Unit) and could form the basis for an international standard. Thirdly, the investigators aim to correlate our findings to clinical severity judged by oxygenation status on arrival in ED. To the investigators' knowledge, this is the first study of this kind.

Full description

COVID-19 is a new disease significant morbidity and mortality which has reached pandemic status. Due to its highly contagious nature, is essential to characterise the disease pathology quickly and reliably. The lung changes that can be seen in patients with COVID-19 can precede clinical symptoms and are picked up on ultrasound more reliably than on conventional chest XR. In addition, ultrasound is devoid of harmful radiation, is quick to perform, and easily learned by doctors who routinely use ultrasound such as in the Emergency Department. To date, there is no data systematically analysing the ultrasound changes in COVID-19 and relating this to disease severity. The data from our study will be contribute significantly to developing strategies for safe triage with regards to cohorting, diagnosis and prognosis of COVID-19.

In this research study, lung ultrasound scans will be retrospectively analysed that were obtained from patients who presented to the emergency department during March-May 2020 with shortness of breath, who were subsequently diagnosed with COVID-19 either by PCR test or composite diagnostic criteria of lymphopenia and positive Chest XR or CT scan report.

The lung ultrasound images will be retrospectively scored for the presence of absence of 5 lung abnormalities (pleural irregularity, B lines, small peripheral consolidation, large consolidation, small effusion (<1cm) and large effusion (>1cm). Scoring will be performed by 2 independent observers with experience in lung ultrasound. In addition, each abnormality will be analysed for preferential location within the lung.

The patients will be grouped into 4 groups of clinical severity (normal oxygenation, mild, moderate and severe deficit in oxygenation) based on the BERLIN criteria for ARDS, and lung abnormalities as seen on lung ultrasound will be analysed for correlation to clinical severity.

Enrollment

43 patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Presented to the ED between March-May 2020 with dyspnoea
  • COVID-19 positive either by PCR test or composite diagnostic criteria of lymphopenia and positive Chest XR report
  • Received lung ultrasound as part of investigations during ED attendance

Exclusion criteria

  • < 18 years of age
  • Not diagnosed with COVID-19

Trial design

43 participants in 4 patient groups

Normal oxygenation
Description:
Normal oxygenation based on the BERLIN criteria for ARDS
Mild deficit in oxygenation
Description:
Mild deficit in oxygenation based on the BERLIN criteria for ARDS
Moderate deficit in oxygenation
Description:
Moderate deficit in oxygenation based on the BERLIN criteria for ARDS
Severe deficit in oxygenation
Description:
Severe deficit in oxygenation based on the BERLIN criteria for ARDS

Trial contacts and locations

1

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Data sourced from clinicaltrials.gov

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