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Predictive Factors COVID-19 Patients (MI-COVID)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04427345
Recruitment Status : Withdrawn (This study has been included in another trial within the same Sponsor)
First Posted : June 11, 2020
Last Update Posted : May 26, 2022
Sponsor:
Information provided by (Responsible Party):
University of Milano Bicocca

Study Description
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Brief Summary:
This is a monocentric retro-prospective observational study that will be conducted on all COVID19 positive patients hospitalized at the S. Gerardo Hospital in Monza.

Condition or disease Intervention/treatment
covid19 Other: Predictive factors for clinical response in patients with COVID-19.

Detailed Description:

BACKGROUND:

The Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) pandemic is severely testing the health systems of the most advanced countries. Clinicians are faced with a new pathology of an emerging virus. There is therefore an urgent need to collect real-time clinical data that informs about outcome predictive variables. Furthermore, there are currently no antiviral drugs approved for the treatment of SARS-CoV-2 infection, off-label therapies are being used with drugs already in use for other pathologies that have shown some efficacy in vitro, and some treatments obtained for compassionate use with other drugs that are being tested.

It is more than ever necessary to collect clinical practice data both retrospectively on the work done so far, and in a longitudinal perspective, and analyze them quickly to optimize current treatments and define protocols for the future. Having a good clinical data base also offers the possibility of collaborating with numerous international networks on translational research, which aims to correlate clinical data with virological and immunological data, aimed at the rapid identification of possible specific viral virulence factors, or particular immune structures of the guests who once again define the final clinical outcome.

STUDY DESIGN:

All COVID19 positive patients admitted to San Gerardo Hospital will be enrolled in the study.

After patient signs the informed consent, the following data will be collected:

  • birth data
  • sex
  • demographic data
  • comorbidity
  • blood chemistry data at the entrance

A series of variables will then be collected relating to the treatment procedure, the therapies, the team's choice to maximize the care ceiling in the individual patient and the entire clinical study of the patient.

STATISTICAL ANALISYS:

Central tendency and dispersion measurements will be used for descriptive analysis of continuous variables while absolute and relative frequencies will be used to describe categorical variables.

Study Design
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Study Type : Observational
Actual Enrollment : 0 participants
Observational Model: Cohort
Time Perspective: Retrospective
Official Title: Predictive Clinical Response Factors in COVID-19 Patients
Actual Study Start Date : April 30, 2020
Estimated Primary Completion Date : May 2021
Actual Study Completion Date : May 12, 2022

Resource links provided by the National Library of Medicine


Groups and Cohorts
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Group/Cohort Intervention/treatment
Covid19 infection related patients
Patients admitted to COVID wards of the S. Gerardo Hospital of Monza, including Intensive Care wards.
 Other: Predictive factors for clinical response in patients with COVID-19.
Identify the risk factors for intra-hospital mortality in patients hospitalized in the COVID + hospital wards of the San Gerardo hospital and build a prognostic score through which it is possible to define a stratification that immediately guides the therapeutic choices and the intensity of care .


Outcome Measures
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Primary Outcome Measures :
  1. Identify risk factors for intra-hospital mortality. [ Time Frame: Until patient discharge from the hospital (approximately 1 year) ]
    Identify risk factors for intra-hospital mortality in patients admitted to the COVID + hospital wards of San Gerardo hospital.

  2. Identify risk factors to build a prognostic score. [ Time Frame: Until patient discharge from the hospital (approximately 1 year) ]
    Identify the risk factors to build a prognostic score through which it is possible to define a stratification that immediately guides the therapeutic choices.

  3. Identify risk factors to build a prognostic score. [ Time Frame: Until patient discharge from the hospital (approximately 1 year) ]
    Identify the risk factors to build a prognostic score through which it is possible to define a stratification that immediately directs towards the right intensity of care.


Secondary Outcome Measures :
  1. Predictive factors for the hospitalization duration. [ Time Frame: Until patient discharge from the hospital (approximately 1 year) ]
    Description of the predictive factors for the hospitalization duration.

  2. Predictive factors for clinical status patients based on "Ordinal Scale for Clinical Improvement" [ Time Frame: Until patient discharge from the hospital (approximately 1 year) ]
    Description of the predictive factors for the clinical status of patients based on "Ordinal Scale for Clinical Improvement" defined by OMS (

  3. Describe the anti-viral therapies used commonly in this emergency in terms of efficacy [ Time Frame: Until patient discharge from the hospital (approximately 1 year). ]
    Description of efficacy of the anti-viral therapies used today without particular restrictions, but on which solid clinical functioning tests are lacking.

  4. Describe the anti-viral therapies used commonly used in this emergency in terms of safety [ Time Frame: Until patient discharge from the hospital (approximately 1 year). ]
    Description of safety of the anti-viral therapies used today without particular restrictions, but on which solid clinical functioning tests are lacking.

  5. Monitor the clinical course of the disease in discharged patients. [ Time Frame: 12 month after discharge ]
    Description of the disease clinical course in patients 12 months after discharge (mortality, neurological, respiratory and cardiac outcomes).


Eligibility Criteria
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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population

The study involves patients admitted to San Gerardo Hospital from March 1, 2020 to May 31, 2020. The minimum expected follow-up will be one year for all patients.

Given the nature of the study, no formal calculation of the sample size was made, nor was a sample size predefined. However, given the recruiting potential of the center which in March saw on average 30-60 hospitalizations due to SARS-CoV-2 per day, even considering a progressive decrease in access, it is assumed that the proportion of patients who will be included in the study will exceed 1000 units.

Criteria

Inclusion Criteria:

  • Patients 18 years old or above
  • Diagnosis of SARS-CoV-2 pneumonia

Exclusion Criteria:

  • Explicit refusal to participate in the study
Contacts and Locations
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Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04427345


Locations
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Italy
ASST Monza-Ospedale San Gerardo
Monza, Italy
Sponsors and Collaborators
University of Milano Bicocca
More Information
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Publications:

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Responsible Party: University of Milano Bicocca
ClinicalTrials.gov Identifier: NCT04427345    
Other Study ID Numbers: MI-COVID
First Posted: June 11, 2020    Key Record Dates
Last Update Posted: May 26, 2022
Last Verified: May 2022
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by University of Milano Bicocca:
Coronavirus
sars-covid-2
coronavirus infection
Additional relevant MeSH terms:
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COVID-19
Respiratory Tract Infections
Infections
Pneumonia, Viral
Pneumonia
Virus Diseases
 Coronavirus Infections
Coronaviridae Infections
Nidovirales Infections
RNA Virus Infections
Lung Diseases
Respiratory Tract Diseases