Selected article for: "admission oxygen saturation and lymphocyte count"

Author: Li, Nan; Kong, Hao; Zheng, Xi-Zi; Li, Xue-Ying; Ma, Jing; Zhang, Hong; Wang, Dong-Xin; Li, Hai-Chao; Liu, Xin-Min
Title: Early predictive factors of progression from severe type to critical ill type in patients with Coronavirus Disease 2019: A retrospective cohort study
  • Cord-id: zmisx1c9
  • Document date: 2020_12_2
  • ID: zmisx1c9
    Snippet: BACKGROUND: The current worldwide pandemic of Coronavirus Disease 2019 (COVID-19) has posed a serious threat to global public health, and the mortality rate of critical ill patients remains high. The purpose of this study was to identify factors that early predict the progression of COVID-19 from severe to critical illness. METHODS: This retrospective cohort study included adult patients with severe or critical ill COVID-19 who were consecutively admitted to the Zhongfaxincheng campus of Tongji
    Document: BACKGROUND: The current worldwide pandemic of Coronavirus Disease 2019 (COVID-19) has posed a serious threat to global public health, and the mortality rate of critical ill patients remains high. The purpose of this study was to identify factors that early predict the progression of COVID-19 from severe to critical illness. METHODS: This retrospective cohort study included adult patients with severe or critical ill COVID-19 who were consecutively admitted to the Zhongfaxincheng campus of Tongji Hospital (Wuhan, China) from February 8 to 18, 2020. Baseline variables, data at hospital admission and during hospital stay, as well as clinical outcomes were collected from electronic medical records system. The primary endpoint was the development of critical illness. A multivariable logistic regression model was used to identify independent factors that were associated with the progression from severe to critical illness. RESULTS: A total of 138 patients were included in the analysis; of them 119 were diagnosed as severe cases and 16 as critical ill cases at hospital admission. During hospital stay, 19 more severe cases progressed to critical illness. For all enrolled patients, longer duration from diagnosis to admission (odds ratio [OR] 1.108, 95% CI 1.022–1.202; P = 0.013), pulse oxygen saturation at admission <93% (OR 5.775, 95% CI 1.257–26.535; P = 0.024), higher neutrophil count (OR 1.495, 95% CI 1.177–1.899; P = 0.001) and higher creatine kinase-MB level at admission (OR 2.449, 95% CI 1.089–5.511; P = 0.030) were associated with a higher risk, whereas higher lymphocyte count at admission (OR 0.149, 95% CI 0.026–0.852; P = 0.032) was associated with a lower risk of critical illness development. For the subgroup of severe cases at hospital admission, the above factors except creatine kinase-MB level were also found to have similar correlation with critical illness development. CONCLUSIONS: Higher neutrophil count and lower lymphocyte count at admission were early independent predictors of progression to critical illness in severe COVID-19 patients.

    Search related documents:
    Co phrase search for related documents
    • acute respiratory distress syndrome and admission lymphocyte count: 1, 2, 3
    • acute respiratory distress syndrome and admission oxygen saturation: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
    • acute respiratory distress syndrome and admission severe illness: 1
    • 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 long duration: 1, 2, 3, 4, 5, 6, 7, 8, 9
    • acute respiratory distress syndrome and low lymphocyte count: 1, 2, 3, 4
    • admission diagnosis 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
    • admission diagnosis and logistic regression analysis: 1, 2, 3, 4, 5, 6, 7, 8, 9
    • admission diagnosis and logistic regression model: 1, 2, 3, 4, 5, 6
    • admission diagnosis and long duration: 1
    • admission expectoration and logistic regression: 1
    • admission expectoration and logistic regression analysis: 1
    • admission expectoration and logistic regression model: 1
    • admission lymphocyte count and logistic regression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16
    • admission lymphocyte count and logistic regression analysis: 1, 2, 3, 4, 5, 6
    • admission lymphocyte count and logistic regression model: 1, 2, 3, 4, 5
    • admission lymphocyte count and low admission lymphocyte count: 1, 2, 3, 4, 5