Prediction of Unfavourable Outcome in Newly Covid-19 Hospitalized Patient
NCT ID: NCT04412031
Last Updated: 2020-06-02
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
802 participants
OBSERVATIONAL
2019-11-11
2020-05-15
Brief Summary
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In the current pandemic context, medical resources have often been exceeded. Developing, using artificial intelligence techniques, an algorithm capable of detecting patients at risk of acute respiratory distress following Sars-Cov2 infection could help physicians to optimize the treatment of patients and health decision-makers to optimize resources. Thus, the goal of this project is to create a prediction model using artificial intelligence to predict an unfavorable evolution of Covid-19 at the hospital admission of patients
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Detailed Description
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Conditions
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Study Design
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COHORT
RETROSPECTIVE
Interventions
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non applicable
non applicable
Eligibility Criteria
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Inclusion Criteria
* Volunteer patients, care givers and healthcare professionals in France and hospitals affiliated with the GABRIEL network. Demographic and clinical data will be collected using case-report forms designed especially for the purpose of the project.
* A nasopharyngeal swab will be collected and tested for SARS-CoV2 by RT-PCR.
* Admission to hospital
Exclusion Criteria
* Patients protected by the law
18 Years
ALL
No
Sponsors
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Hospices Civils de Lyon
OTHER
Responsible Party
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Locations
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Hôpital E Herriot - Hospices Civils de LYON
Lyon, , France
Countries
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Other Identifiers
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20_185
Identifier Type: -
Identifier Source: org_study_id
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