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Development and validation of a predictive model of in-hospital mortality in COVID-19 patients

Author

Listed:
  • Diego Velasco-Rodríguez
  • Juan-Manuel Alonso-Dominguez
  • Rosa Vidal Laso
  • Daniel Lainez-González
  • Aránzazu García-Raso
  • Sara Martín-Herrero
  • Antonio Herrero
  • Inés Martínez Alfonzo
  • Juana Serrano-López
  • Elena Jiménez-Barral
  • Sara Nistal
  • Manuel Pérez Márquez
  • Elham Askari
  • Jorge Castillo Álvarez
  • Antonio Núñez
  • Ángel Jiménez Rodríguez
  • Sarah Heili-Frades
  • César Pérez-Calvo
  • Miguel Górgolas
  • Raquel Barba
  • Pilar Llamas-Sillero

Abstract

We retrospectively evaluated 2879 hospitalized COVID-19 patients from four hospitals to evaluate the ability of demographic data, medical history, and on-admission laboratory parameters to predict in-hospital mortality. Association of previously published risk factors (age, gender, arterial hypertension, diabetes mellitus, smoking habit, obesity, renal failure, cardiovascular/ pulmonary diseases, serum ferritin, lymphocyte count, APTT, PT, fibrinogen, D-dimer, and platelet count) with death was tested by a multivariate logistic regression, and a predictive model was created, with further validation in an independent sample. A total of 2070 hospitalized COVID-19 patients were finally included in the multivariable analysis. Age 61–70 years (p 80 years (p 2 ULN (p = 0.003; OR: 1.79; 95%CI: 1.22 to 2.62), and prolonged PT (p

Suggested Citation

  • Diego Velasco-Rodríguez & Juan-Manuel Alonso-Dominguez & Rosa Vidal Laso & Daniel Lainez-González & Aránzazu García-Raso & Sara Martín-Herrero & Antonio Herrero & Inés Martínez Alfonzo & Juana Serrano, 2021. "Development and validation of a predictive model of in-hospital mortality in COVID-19 patients," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-12, March.
    • Handle: RePEc:plo:pone00:0247676
    DOI: 10.1371/journal.pone.0247676
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