A study on the factors influencing the transfer of COVID-19 severe illness patients out of the ICU based on generalized linear mixed effect model

Math Biosci Eng. 2022 Jul 25;19(10):10602-10617. doi: 10.3934/mbe.2022495.

Abstract

The clinical data of 76 severe illness patients with novel coronavirus SARS-CoV-2 from July to August, 2020 admitted to the ICU Intensive Care Unit ward in a hospital in Urumqi were collected in the paper. By using the Laplace approximation parameter estimation method based on maximum likelihood estimation, the generalized linear mixed effect model (GLMM) was established to analyze the characteristics of clinical indicators in critical patients, and to screen the main influencing factors of COVID-19 critical patients' inability to be transferred out of the ICU in a short time: age, C-reactive protein, serum creatinine and lactate dehydrogenase.

Keywords: critically ill patients; generalized linear mixed effect model; maximum likelihood estimate; novel coronavirus(SARS-CoV-2).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19*
  • Critical Illness
  • Hospitalization
  • Humans
  • Intensive Care Units
  • SARS-CoV-2