Selected article for: "clinical disease evidence and disease cause"

Author: Liu, Hanqing; Ruan, Zhouru; Yin, Ziwei; Wu, Dan; Zhu, Hong
Title: Association of administration of IFN-α with mortality among patients hospitalized with coronavirus disease 2019
  • Cord-id: 6sz1ss9d
  • Document date: 2021_3_3
  • ID: 6sz1ss9d
    Snippet: Aim: Recent studies on coronavirus disease 2019 (COVID-19) have not offered sufficient clinical evidence to support whether IFN-α can decrease the mortality of patients with COVID-19. Method: In this retrospective study, 103 of 1555 hospitalized COVID-19 patients were treated with IFN-α, and the others matched through propensity score matching. Cox regression model, logistics analysis and Kaplan–Meier statistics depicted the survival curve. Results & conclusion: Single factor analysis demons
    Document: Aim: Recent studies on coronavirus disease 2019 (COVID-19) have not offered sufficient clinical evidence to support whether IFN-α can decrease the mortality of patients with COVID-19. Method: In this retrospective study, 103 of 1555 hospitalized COVID-19 patients were treated with IFN-α, and the others matched through propensity score matching. Cox regression model, logistics analysis and Kaplan–Meier statistics depicted the survival curve. Results & conclusion: Single factor analysis demonstrated that fewer deaths occurred in patients treated with IFN-α compared with patients treated without IFN-α (p = 0.000). Logistics analysis showed that patients treated with IFN-α had an all-cause mortality odds ratio = 0.01 (95% CI: 0.001–0.110; p = 0.000). The Cox regression model was utilized to determine an all-cause mortality with a hazard ratio of 0.102 (95% CI: 0.030–0.351; p = 0.000). IFN-α can alleviate disease severity and decrease all-cause mortality, especially in critical patients. IFN-α could effectively treat patients with COVID-19.

    Search related documents:
    Co phrase search for related documents
    • absolute value and admission time: 1, 2, 3
    • absolute value and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9
    • absolute value and logistic regression analysis: 1, 2, 3, 4
    • absolute value and logistic regression model: 1, 2, 3
    • acute liver injury and admission time: 1, 2, 3, 4
    • acute liver injury and liver injury: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • acute liver injury and logistic regression: 1, 2, 3, 4, 5, 6
    • acute liver injury and logistic regression analysis: 1
    • acute liver injury and lopinavir ritonavir: 1
    • acute respiratory distress syndrome and adaptive immune system: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
    • acute respiratory distress syndrome and admission time: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • acute respiratory distress syndrome and liver injury: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • acute respiratory distress syndrome and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • acute respiratory distress syndrome and logistic regression analysis: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • acute respiratory distress syndrome and logistic regression model: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
    • acute respiratory distress syndrome and lopinavir ritonavir: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
    • acute respiratory distress syndrome and low cause mortality: 1
    • acute respiratory distress syndrome and low level expression: 1
    • acute respiratory distress syndrome and lung peripheral blood: 1, 2, 3