IDEAS home Printed from https://ideas.repec.org/a/epw/ejmed0/v2y2020i2id40233.html

Can the Oxidative Stress Index Predict the Severity of COVID-19?

Author

Listed:
  • Harold I Zeliger

    (Zeliger Research and Consulting, USA.)

  • Harvey Kahaner

    (Zeliger Research and Consulting, USA.)

Abstract

Severity of the COVID-19 disease ranges from imperceptible to death with the aged and those with pre-existing conditions being particularly vulnerable to severe symptoms. Other factors have also been shown to influence COVID-19 severity. These include smoking, vaping and exposure to air pollution. These factors have a one thing in common, all raise oxidative stress. The Oxidative Stress Index, derived from a questionnaire and reflective of oxidative stress level, is proposed as a non-invasive way to predict the severity of COVID-19 in those impacted by the Coronavirus.

Suggested Citation

  • Harold I Zeliger & Harvey Kahaner, 2020. "Can the Oxidative Stress Index Predict the Severity of COVID-19?," European Journal of Medical and Health Sciences, European Open Science, vol. 2(2), March.
  • Handle: RePEc:epw:ejmed0:v:2:y:2020:i:2:id:40233
    DOI: 10.24018/ejmed.2020.2.2.233
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejmed/article/view/40233
    File Function: Abstract page
    Download Restriction: no

    File URL: https://eu-opensci.org/index.php/ejmed/article/download/40233/8857
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.24018/ejmed.2020.2.2.233?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:epw:ejmed0:v:2:y:2020:i:2:id:40233. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejmed .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.