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Data_Sheet_1_Early predictors of intensive care unit admission among COVID-19 patients in Qatar.DOCX

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NIAID Data Ecosystem2026-05-01 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Early_predictors_of_intensive_care_unit_admission_among_COVID-19_patients_in_Qatar_DOCX/25440430
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BackgroundCOVID-19 is associated with significant morbidity and mortality. This study aimed to explore the early predictors of intensive care unit (ICU) admission among patients with COVID-19. MethodsThis was a case–control study of adult patients with confirmed COVID-19. Cases were defined as patients admitted to ICU during the period February 29–May 29, 2020. For each case enrolled, one control was matched by age and gender. ResultsA total of 1,560 patients with confirmed COVID-19 were included. Each group included 780 patients with a predominant male gender (89.7%) and a median age of 49 years (interquartile range = 18). Predictors independently associated with ICU admission were cardiovascular disease (adjusted odds ratio (aOR) = 1.64, 95% confidence interval (CI): 1.16–2.32, p = 0.005), diabetes (aOR = 1.52, 95% CI: 1.08–2.13, p = 0.016), obesity (aOR = 1.46, 95% CI: 1.03–2.08, p = 0.034), lymphopenia (aOR = 2.69, 95% CI: 1.80–4.02, p < 0.001), high AST (aOR = 2.59, 95% CI: 1.53–4.36, p < 0.001), high ferritin (aOR = 1.96, 95% CI: 1.40–2.74, p < 0.001), high CRP (aOR = 4.09, 95% CI: 2.81–5.96, p < 0.001), and dyspnea (aOR = 2.50, 95% CI: 1.77–3.54, p < 0.001). ConclusionHaving cardiovascular disease, diabetes, obesity, lymphopenia, dyspnea, and increased AST, ferritin, and CRP were independent predictors for ICU admission in patients with COVID-19.
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2024-03-20
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