Tomographic Findings in COVID-19 and Influenza (TOMOCOVIDMX)

August 4, 2020 updated by: Jaime Daniel Mondragón Uribe, Universidad de Guanajuato

Pulmonary Tomographic Findings in COVID-19 and Influenza H1N1 Patients

The investigators decided to conduct a longitudinal study that compares the pulmonary tomographic patterns found in patients with viral pneumonia (i.e. influenza H1N1 and SARS-CoV-2) at a regional hospital. The primary aim of this study is to compare the radiological patterns found in patients with COVID-19 and influenza H1N1. The secondary aims of this study will assess the association between the radiological CT pattern and the need for invasive mechanical ventilation and mortality within the first 28 days of intensive care unit admission.

Study Overview

Status

Unknown

Conditions

Intervention / Treatment

Detailed Description

Background

In late 2019, a new coronavirus was linked to several cases of pneumonia in the city of Wuhan, Hubei province, China. On February 11, 2020, the World Health Organization (WHO) designated COVID-19 a pandemic disease. The mortality associated with COVID-19 patients that required management in a critical care unit is approximately 4.3%. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Diagnosis of COVID-19 is made with a positive test (i.e. reverse transcriptase-polymerase chain reaction, RT-PCR) from a person with clinical signs and symptoms of a respiratory tract infection. Viral pneumonia is currently a challenge worldwide as it is associated with high morbidity and mortality. In June of 2009, the WHO declared influenza A H1N1 a pandemic disease. Worldwide, influenza H1N1 had a mortality of 11%, with a higher mortality rate among people older than 50 years of age (i.e. 18-20%). Influenza diagnosis can be established using RT-PCR. Around 200 million cases of community-acquired viral pneumonia occur each year worldwide, 100 million in children, and 100 million in adults. Imaging findings in viral pneumonia are diverse and overlap with findings associated with non-viral infections and inflammatory conditions. However, identifying the underlying viral pathogens may not always be easy. Several imaging patterns have been described in association with these viruses. Although a definitive diagnosis cannot be achieved based on imaging studies, imaging pattern recognition of viral pneumonia can help differentiate between viral and bacterial pathogens; thus, reducing the use of indiscriminate antibiotics. There are few studies that correlate tomographic findings in patients with viral infections in the lower respiratory tract.

The use of computed tomography (CT) should be considered as the first option for diagnostic imaging in patients with suspected pneumonia. Peripheral multifocal ground glass patterns with irregular consolidation images found in the lower lobes or posteriorly in pulmonary CT scans have been described in patients with viral pneumonia due to SARS-CoV-2. Furthermore, complicating the diagnosis of atypical viral pneumonia, 17.9% of mild COVID-19 and 2.9% of moderate-severe COVID-19 patients did not have CT evidence of pneumonia upon hospital admission. One recent study compared the CT radiological patterns found in COVID-19 pneumonia to other viral pneumonias (i.e. influenza, parainfluenza, adenovirus, and respiratory syncytial virus) reporting higher peripheral distribution (i.e. 80% vs. 57%, p<0.001), more ground-glass opacities (i.e. 91% vs 68%, p<0.001), greater frequency of fine reticular opacities (i.e. 56% vs. 22%, p<0.001), and vascular thickening in COVID-19 patients; meanwhile, other viral pneumonias were more likely to have a mixed distribution pattern(i.e. 35% vs. 14%, p<0.001), have pleural effusion (i.e. 39% vs. 4.1%, p<0.001), and present visible lymph nodes (10.2% vs. 2.7%, p<0.001). Another study compared the pulmonary radiological patterns associated with COVID-19 compared to influenza (A and B) reporting higher round opacities (i.e. 35% vs. 17%, p=0.048) and greater frequency of interlobular septal thickening (i.e. 66% vs. 43%, p=0.014) in patients with COVID-19; conversely, influenza patients had a higher frequency of nodular lesions (i.e. 71% vs. 28%, p<0.001), higher frequency of small dense nodular lesions (i.e. 40% vs. 9%, p<0.001), and more likely to have pleural effusion (i.e. 31% vs. 6%, p<0.001).

Research questions

  1. What are the pulmonary tomographic findings in patients diagnosed with community-acquired pneumonia secondary to SARS-CoV-2?
  2. What are the pulmonary tomographic findings in patients diagnosed with community-acquired pneumonia secondary to H1N1 influenza?
  3. Are the 28-day survival distributions different for SARS-CoV-2 and H1N1 influenza?
  4. Is there a difference in the 28-day survival distribution and the pulmonary tomographic radiological patterns in patients with pneumonia secondary to SARS-CoV-2?
  5. Is there a difference in the 28-day survival distribution and the pulmonary tomographic radiological patterns in patients with pneumonia secondary to H1N1 influenza?
  6. What factors are associated with the survival differences in 28-day mortality in both groups and between groups?

Study Type

Observational

Enrollment (Anticipated)

100

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Mexico
    • Guanajuato
      • León, Guanajuato, Mexico, 37672
        • Recruiting
        • Hospital General León-Milenio
        • Contact:
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 80 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Convenience sample from a Mexican urban, suburban, and rural population. The patients come from all demographical and socio-economic strata from a country with a high (0.767) Human Development Index. Our hospital is open to the entire population and primarily assists people with limited to very limited resources.

Description

Inclusion Criteria:

  • Patients with signed informed consent.
  • Patients with a positive PCR test for SARS-CoV-2 or influenza H1N1 test upon emergency department admission.
  • Patients with lung CT within 24hrs of specimen collection for PCR test.
  • Patients with complete 30-day follow-up information.

Exclusion Criteria:

  • Patients who are unwilling to undergo a lung CT.
  • Negative PCR test for SARS-CoV-2 or influenza H1N1 test upon emergency department admission.
  • Patients with a tumor or tumor metastasis on the pulmonary CT.
  • Patients with a previous or de novo autoimmune disease diagnosis.
  • Patients with a previous or de novo interstitial lung disease.
  • Pregnancy.

Elimination Criteria:

  • Patients with loss of information on the variables of interest.
  • Patients without 30-day follow-up information.
  • Patients who chose to withdraw their participation at any time of the study.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Prospective

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
SARS-CoV-2
Patients with a SARS-CoV-2 polymerase chain reaction positive test upon admission to the emergency department.
Diagnostic test: Thoraxic computed tomography
Diagnostic lung CT.
H1N1 influenza
Patients with an influenza H1N1 polymerase chain reaction positive test upon admission to the emergency department.
Diagnostic test: Thoraxic computed tomography
Diagnostic lung CT.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Radiological findings
Time Frame: 24 hours
Lung CT radiological patterns associated with COVID-19 or Influenza H1N1
24 hours

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Survival
Time Frame: 28 days
Intrahospital and overall survival at 28 days from hospital admission.
28 days

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Universidad de Guanajuato

Collaborators

University Medical Center Groningen
Hospital General Regional de León

Investigators

  • Principal Investigator: Omar Jiménez-Zarazúa, M.D., Medical researcher, Internist

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 15, 2020

Primary Completion (Anticipated)

April 30, 2021

Study Completion (Anticipated)

April 30, 2022

Study Registration Dates

First Submitted

July 31, 2020

First Submitted That Met QC Criteria

August 3, 2020

First Posted (Actual)

August 4, 2020

Study Record Updates

Last Update Posted (Actual)

August 6, 2020

Last Update Submitted That Met QC Criteria

August 4, 2020

Last Verified

August 1, 2020

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • HGL-ENSE-00743-20

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

Undecided

IPD Plan Description

A database will be generated and available upon request. All patients will de unidentified.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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