• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

J Med Virol . Inflammation-associated factors for predicting in-hospital mortality in patients with COVID-19

tetano

Editor, Senior Moderator
J Med Virol


. 2021 Jan 4.
doi: 10.1002/jmv.26771. Online ahead of print.
Inflammation-associated factors for predicting in-hospital mortality in patients with COVID-19


Jun-Hong Wang[SUP] 1 [/SUP], Ru-Dong Chen[SUP] 1 [/SUP], Hong-Kuan Yang[SUP] 1 [/SUP], Ling-Cheng Zeng[SUP] 1 [/SUP], Hao Chen[SUP] 1 [/SUP], Yu-Yang Hou[SUP] 1 [/SUP], Wei Hu[SUP] 1 [/SUP], Jia-Sheng Yu[SUP] 1 [/SUP], Hua Li[SUP] 1 [/SUP]



Affiliations

Abstract

Objectives: To explore the relation between inflammation-associated factors and in-hospital mortality and investigate which factor is an independent predictor of in-hospital death in patients with coronavirus disease-2019.
Methods: This study included patients with coronavirus disease-2019 who were hospitalized between February 9, 2020, and March 30, 2020. Univariate Cox regression analysis and least absolute shrinkage and selection operator regression (LASSO) were used to select variables. Multivariate Cox regression analysis was applied to identify independent risk factors in coronavirus disease-2019.
Results: 1135 patients were analysed during the study period. A total of 35 variables were considered to be risk factors after the univariate regression analysis of the clinical characteristics and laboratory parameters (p < 0.05), and LASSO regression analysis screened out seven risk factors for further study. The six independent risk factors revealed by multivariate Cox regression were myoglobin (HR 5.353, 95% CI 2.633-10.882; p < 0.001), C-reactive protein (HR 2.063, 95% CI 1.036-4.109; p = 0.039), neutrophil count (HR 2.015, 95% CI 1.154-3.518; p = 0.014), interleukin 6 (HR 9.753, 95% CI 2.952-32.218; p < 0.001), age (HR 2.016, 95% CI 1.077-3.773; p = 0.028), and international normalized ratio (HR 2.595, 95% CI 1.412-4.769; p = 0.002).
Conclusion: Our results suggested that inflammation-associated factors were significantly associated with in-hospital mortality in coronavirus disease-2019 patients. C-reactive protein, neutrophil count and interleukin 6 were independent factors for predicting in-hospital mortality and had a better independent predictive ability. We believe these findings may allow early identification of the patients at high risk for death, and can also assist better management of these patients. This article is protected by copyright. All rights reserved.

Keywords: C-reactive protein; Coronavirus disease-2019 (COVID-19); Cytokine profiles; Interleukin 6; Neutrophil count; in-hospital mortality.
 
Back
Top Bottom