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Completed

NCT Number: NCT04953247

Use of Compromised Lung Volume in Monitoring Usage of Steroid Therapy on Severe COVID-19

Since December 2019, the outbreak of coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. Although corticosteroid therapy represents a milestone in the management of COVID-19, many questions remain unanswered. The optimal type of corticosteroids, timing of initiation, dose, mode of administration, duration, and dose tapering are still unclear. An approach to resolve these issues is to develop accurate tools to assess or monitor the progression of COVID-19 during the corticosteroid therapy process. Quantitative computed tomography (QCT) analysis may serve as a tool for assessing the severity of COVID-19 and for monitoring its progress. However, the effect of steroids on quantitative chest CT parameters during the treatment process remains unknown. In this retrospectively study, we aimed to assess the association between steroid administration and QCT variables in a longitudinal cohort with COVID-19

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Key information

Conditions

COVID-19 Pneumonia COVID-19 Coronaviridae Infections Coronavirus Infections Infections Lung Diseases Nidovirales Infections Pneumonia Pneumonia, Viral Quantitative Computed Tomography RNA Virus Infections Respiratory Tract Diseases Respiratory Tract Infections Virus Diseases

Age range

18 year–90 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Zhongshan hospital, Fudan university

Shanghai, China

About this study

Since December 2019, the outbreak of coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern. Although corticosteroid therapy represents a milestone in the management of COVID-19, many questions remain unanswered. The optimal type of corticosteroids, timing of initiation, dose, mode of administration, duration, and dose tapering are still unclear. An approach to resolve these issues is to develop accurate tools to assess or monitor the progression of COVID-19 during the corticosteroid therapy process. Quantitative computed tomography (QCT) analysis may serve as a tool for assessing the severity of COVID-19 and for monitoring its progress. However, the effect of steroids on quantitative chest CT parameters during the treatment process remains unknown. In this retrospectively study, we aimed to assess the association between steroid administration and QCT variables in a longitudinal cohort with COVID-19.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • (1) age 18-90 years
  • (2) patients with severe or critical COVID-19.

Exclusion criteria

  • (1) hematological or solid malignancies
  • (2) patients with less than two CT scans during hospital stay
  • (3) systemic corticosteroid or immunosuppressive therapy in the previous 6 weeks.

Treatment and study plan

Primary outcomes

  1. Changes in the percentage of compromised lung volume (Δ%CL) at different stages

    Time frame: 31 days

    According to different Hounsfield unit (HU) intervals in the quantitative chest CT scan, we divided each lung into nonaerated lung volume (%NNL, 100 to -100 HU), poorly aerated lung volume (%PAL, -101 to -500 HU), normally aerated lung volume (%NAL, -501 to -900 HU), and hyperinflated lung volume (%HI, -901 to -1000 HU) regions. The additional "compromised lung" volume (%CL) was considered as the sum of %PAL and %NNL (-500 to 100 HU).

    To monitor COVID-19 progression during the treatment process, we chose changes in the percentage of compromised lung volume (Δ%CL) at different stages (Δ%CL = %CL at different stages-baseline %CL) as the primary outcome. The negative value of Δ%CL thus reflected clinical improvement.

Secondary outcomes

  1. Changes in the percentage of NNL at different stages

    Time frame: 31 days

    According to different Hounsfield unit (HU) intervals in the quantitative chest CT scan, we divided each lung into nonaerated lung volume (%NNL, 100 to -100 HU), poorly aerated lung volume (%PAL, -101 to -500 HU), normally aerated lung volume (%NAL, -501 to -900 HU), and hyperinflated lung volume (%HI, -901 to -1000 HU) regions.

  2. Changes in the percentage of PAL at different stages

    Time frame: 31 days

    According to different Hounsfield unit (HU) intervals in the quantitative chest CT scan, we divided each lung into nonaerated lung volume (%NNL, 100 to -100 HU), poorly aerated lung volume (%PAL, -101 to -500 HU), normally aerated lung volume (%NAL, -501 to -900 HU), and hyperinflated lung volume (%HI, -901 to -1000 HU) regions. Under these circumstances, clinical improvement was reflected by the negative value of Δ%NNL and Δ%PAL, and the positive value of Δ%NAL.

  3. Changes in the percentage of NAL at different stages

    Time frame: 31 days

    According to different Hounsfield unit (HU) intervals in the quantitative chest CT scan, we divided each lung into nonaerated lung volume (%NNL, 100 to -100 HU), poorly aerated lung volume (%PAL, -101 to -500 HU), normally aerated lung volume (%NAL, -501 to -900 HU), and hyperinflated lung volume (%HI, -901 to -1000 HU) regions. Under these circumstances, clinical improvement was reflected by the negative value of Δ%NNL and Δ%PAL, and the positive value of Δ%NAL.

  4. Changes in the percentage of HL at different stages

    Time frame: 31 days

    According to different Hounsfield unit (HU) intervals in the quantitative chest CT scan, we divided each lung into nonaerated lung volume (%NNL, 100 to -100 HU), poorly aerated lung volume (%PAL, -101 to -500 HU), normally aerated lung volume (%NAL, -501 to -900 HU), and hyperinflated lung volume (%HI, -901 to -1000 HU) regions. Under these circumstances, clinical improvement was reflected by the negative value of Δ%NNL and Δ%PAL, and the positive value of Δ%NAL.

Sponsors and collaborators

Lead sponsor

Guowei Tu

Other

Registry information

Important dates

Study start
2020
Primary completion
2020
Study completion
2021
First posted
Jul 7, 2021
Registry last updated
Jul 8, 2021

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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