five

Multivariate logistic regression.

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NIAID Data Ecosystem2026-03-14 收录
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https://figshare.com/articles/dataset/Multivariate_logistic_regression_/22195615
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Objective The aim of this study is to explore the role of IL6 in predicting outcome in critically ill COVID-19 patients. Design Prospective observational cohort study. Setting 20-bed respiratory medical intensive care unit of Abderrahmen Mami Teaching Hospital between September and December 2020. Methods We included all critically ill patients diagnosed with COVID-19 managed in ICU. IL6 was measured during the first 24 hours of hospitalization. Results 71 patients were included with mean age of 64 ± 12 years, gender ratio of 22. Most patients had comorbidities, including hypertension (n = 32, 45%), obesity (n = 32, 45%) and diabetes (n = 29, 41%). Dexamethasone 6 mg twice a day was initiated as treatment for all patients. Thirty patients (42%) needed high flow oxygenation; 59 (83%) underwent non-invasive ventilation for a median duration 2 [1–5] days. Invasive mechanical ventilation was required in 44 (62%) patients with a median initiation delay of 1 [0–4] days. Median ICU length of stay was 11 [7–17] days and overall mortality was 61%. During the first 24 hours, median IL6 was 34.4 [12.5–106] pg/ml. Multivariate analysis shows that IL-6 ≥ 20 pg/ml, CPK < 107 UI/L, AST < 30 UI/L and invasive ventilation requirement are independent risk factors for mortality. Conclusions IL-6 is a strong mortality predictor among critically ill COVID19 patients. Since IL-6 antagonist agents are costly, this finding may help physicians to consider patients who should benefit from that treatment.
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2023-03-01
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