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S1 Data -

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/S1_Data_-/26120098
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The Coronavirus Disease 2019 (COVID-19) has caused a global health crisis. Mortality predictors in critically ill patients remain under investigation. A retrospective cohort study included 201 patients admitted to the intensive care unit (ICU) due to COVID-19. Data on demographic characteristics, laboratory findings, and mortality were collected. Logistic regression analysis was conducted with various independent variables, including demographic characteristics, clinical factors, and treatment methods. The study aimed to identify key risk factors associated with mortality in an ICU. In an investigation of 201 patients comprising non-survivors (n = 80, 40%) and Survivors (n = 121, 60%), we identified several markers significantly associated with ICU mortality. Lower Interleukin 6 and White Blood Cells levels at both 24- and 48-hours post-ICU admission emerged as significant indicators of survival. The study employed logistic regression analysis to evaluate risk factors for in-ICU mortality. Analysis results revealed that demographic and clinical factors, including gender, age, and comorbidities, were not significant predictors of in-ICU mortality. Ventilator-associated pneumonia was significantly higher in Survivors, and the use of antibiotics showed a significant association with increased mortality risk in the multivariate model (OR: 11.2, p = 0.031). Our study underscores the significance of monitoring Il-6 and WBC levels within 48 hours of ICU admission, potentially influencing COVID-19 patient outcomes. These insights may reshape therapeutic strategies and ICU protocols for critically ill patients.
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2024-06-27
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