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

Zemin Luan; Zhaoxia Yu; Ting Zeng; Rui Wang; Maozai Tian; Kai Wang; Zemin Luan; Zhaoxia Yu; Ting Zeng; Rui Wang; Maozai Tian; Kai Wang

doi:10.3934/mbe.2022495

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 10: 10602-10617. doi: 10.3934/mbe.2022495

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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

1.
School of Public Health, Xinjiang Medical University, Urumqi 830017, China
2.
Department of Critical Care Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China
3.
College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China
4.
Department of Trauma Intensive Care Unit, the first affiliated hospital of Xinjiang medical university, Urumqi 830054, China
^† These authors contributed equally.

Received: 22 April 2022 Revised: 09 July 2022 Accepted: 14 July 2022 Published: 25 July 2022

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.
- novel coronavirus(SARS-CoV-2),
- critically ill patients,
- generalized linear mixed effect model,
- maximum likelihood estimate
Citation: Zemin Luan, Zhaoxia Yu, Ting Zeng, Rui Wang, Maozai Tian, Kai Wang. 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[J]. Mathematical Biosciences and Engineering, 2022, 19(10): 10602-10617. doi: 10.3934/mbe.2022495

Related Papers:

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.

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