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Lung Ultrasound for COVID-19 Initial Triage and Monitoring

Use of Lung Ultrasound for COVID-19 Patient's Initial Triage Assessment and Early Monitoring: a Pilot Study

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT04474236
Acronym
QUICK
Enrollment
25
Registered
2020-07-16
Start date
2020-05-27
Completion date
2021-03-07
Last updated
2021-06-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Acute Respiratory Failure, COVID-19, CT Scan, Lung Ultrasound, Triage

Keywords

COVID-19, Acute Respiratory Failure, Triage, Lung Ultrasound, CT scan

Brief summary

The QUICK study main aim is to assess the predictive value at Day 1, of a model built on lung ultrasound (LUS) and clinical data, both recorded at hospital admission of COVID-19 patients.

Detailed description

Initial triage assessment is the cornerstone of first-line medical management for COVID-19 patients. Only an accurate and fast evaluation of COVID-19 patients respiratory system integrity, can allow optimal treatment care and medical resources attribution. Despite its very large deployment, the use of thoracic Computed Tomography (CT scan) for COVID-19 patients severity assessment is currently debated. Actually CT-scan use in this setting: i) it is associated with risky in/out hospital patient's transport, both in terms of medical management of patient's critical conditions and risk of COVID-19 nosocomial transmission, ii) risks related to x-ray exposure iii) CT-scan is a snapshot of respiratory system integrity and does not provide data that might be used for patient's monitoring. LUS is a non-invasive, non-ionizing, fully bedside imaging tool. Investigators team has previously contributed to the development and validation of LUS for critically ill patient's management. To the extent of our knowledge, there is neither data regarding COVID-19 patient's LUS patterns, nor about the potential link between LUS data, patient's severity and outcome. The investigators hypothesize that the combined use of LUS and clinical data (Q-SOFA score, SpiO2/FiO2) recorded at COVID-19 patients hospital admission, will allow to accurately predict short-term outcome. The investigators expect to predict at patient's hospital admission, the patient's clinical status at 24h: favorable (spontaneous ventilation with O2 \< 6 l/min) or unfavorable (spontaneous ventilation with O2 \> 6 l/min or under mechanical ventilation).

Interventions

OTHERthoracic lung ultrasound

Patients will be recruited the day of their hospital admission. All patients will be assessed by thoracic Computed Tomography scan then immediately before/after CT scan, patients will be clinically assessed (Q-SOFA, SpiO2/FiO2) and a lung ultrasound evaluation (mean time of evaluation 7 min +/- 3 min; fully respect of COVID-19 barrier measures) will be performed by an investigator. Patients clinical status and outcomes will be extracted from patient's medical file at day 1 and day 28 from patient's admission by investigators blinded from previously recorded lung ultrasound data.

Sponsors

University Hospital, Toulouse
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
17 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Adult (\> 18 years). * Proven COVID-19 (specific PCR from respiratory track sample) * CT scan prescribed by physician in charge, independently of research. * Patients consent (or surrogate decision maker's consent in case of need).

Exclusion criteria

* Reduction or cessation of active treatment. * Patient under guardianship, tutelage measure or judicial protection * Patient deprived of liberty by judicial order * No French health insurance. * Pregnancy or nursing woman. * Enrolled in another trial evaluating thoracic imaging.

Design outcomes

Primary

MeasureTime frameDescription
Area Under the Curve (AUC) of a predictive model built on LUS and clinical (Q-SOFA, SpiO2/FiO2) dataDay 1Area Under the Curve (AUC) of a predictive model at 24h from hospital admission (Favorable vs Unfavorable), built on LUS (12 thoracic regions) and clinical (Q-SOFA, SpiO2/FiO2) data recorded at hospital admission.

Secondary

MeasureTime frameDescription
Area Under the Curve (AUC) of a predictive model built on CT scan and clinical (Q-SOFA, SpiO2/FiO2) dataDay 1Area Under the Curve (AUC) of a predictive model at 24h from hospital admission (Favorable vs Unfavorable), built on CT scan and clinical (Q-SOFA, SpiO2/FiO2) data recorded at hospital admission.
mortalityDay 28mortality

Countries

France

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026