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CODE - Early detection of exacerbation in COVID-19 patients (through ongoing oxygen and CO2 measurements combined with artificial intelligence)

Grant number: unknown

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Key facts

  • Disease

    COVID-19

  • Start & end year

    N/A

  • Funder

    Innovationsfonden Denmark

  • Research Location

    Denmark

  • Lead Research Institution

    University of Copenhagen, Radiometer and Herlev-Gentofte Hospital

  • Research Priority Alignment

    N/A

  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Supportive care, processes of care and management

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

An algorithm, supported by artificial intelligence, that can detect any worsening of symptoms in COVID-19 patients, is the goal of a new study by the University of Copenhagen, Radiometer and Herlev-Gentofte Hospital. In order for doctors and nurses to intervene as soon as possible with the correct treatment of COVID-19 patients, a new algorithm is being developed that can identify patients who are at risk of hypoxia (a condition of oxygen deficiency in the patient). By continuously measuring O2 and CO2 via sensors on the skin, a supplement to traditional blood gas measurement, doctors and nurses will be able to decide which treatment is needed.