IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0293476.html
   My bibliography  Save this article

Prediction model for in-hospital mortality in patients at high altitudes with ARDS due to COVID-19

Author

Listed:
  • David Rene Rodriguez Lima
  • Cristhian Rubio Ramos
  • Andrés Felipe Yepes Velasco
  • Leonardo Andrés Gómez Cortes
  • Darío Isaías Pinilla Rojas
  • Ángela María Pinzón Rondón
  • Ángela María Ruíz Sternberg

Abstract

Introduction: The diagnosis of acute respiratory distress syndrome (ARDS) includes the ratio of pressure arterial oxygen and inspired oxygen fraction (P/F) ≤ 300, which is often adjusted in locations more than 1,000 meters above sea level (masl) due to hypobaric hypoxemia. The main objective of this study was to develop a prediction model for in-hospital mortality among patients with ARDS due to coronavirus disease 2019 (COVID-19) (C-ARDS) at 2,600 masl with easily available variables at patient admission and to compare its discrimination capacity with a second model using the P/F adjusted for this high altitude. Methods: This study was an analysis of data from patients with C-ARDS treated between March 2020 and July 2021 in a university hospital located in the city of Bogotá, Colombia, at 2,600 masl. Demographic and laboratory data were extracted from electronic records. For the prediction model, univariate analyses were performed to screen variables with p

Suggested Citation

  • David Rene Rodriguez Lima & Cristhian Rubio Ramos & Andrés Felipe Yepes Velasco & Leonardo Andrés Gómez Cortes & Darío Isaías Pinilla Rojas & Ángela María Pinzón Rondón & Ángela María Ruíz Sternberg, 2023. "Prediction model for in-hospital mortality in patients at high altitudes with ARDS due to COVID-19," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-16, October.
    • Handle: RePEc:plo:pone00:0293476
    DOI: 10.1371/journal.pone.0293476
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0293476
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0293476&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0293476?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
    ---><---

    References listed on IDEAS

    as
    1. Zhongheng Zhang & Hongying Ni, 2015. "Prediction Model for Critically Ill Patients with Acute Respiratory Distress Syndrome," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-14, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      More about this item

      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:plo:pone00:0293476. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

      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.