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Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China

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单位: [1]Department of Cardiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China [2]Department of Pulmonary Disease, The Third People’s Hospital of Yichang, Yichang, Hubei, China [3]Department of Cardiology Nursing Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China [4]Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China
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关键词: COVID-19 severe or critical symptoms nomogram prediction risk

摘要:
Objectives: We aimed to identify potential risk factors for severe or critical coronavirus disease 2019 (COVID-19) and establish a prediction model based on significant factors. Methods: A total of 370 patients with COVID-19 were consecutively enrolled at The Third People's Hospital of Yichang from January to March 2020. COVID-19 was diagnosed according to the COVID-19 diagnosis and treatment plan released by the National Health and Health Committee of China. Effect-size estimates are summarized as odds ratio (OR) and 95% confidence interval (CI). Results: 326 patients were diagnosed with mild or ordinary COVID-19, and 44 with severe or critical COVID19. After propensity score matching and statistical adjustment, eight factors were significantly associated with severe or critical COVID-19 (p<0.05) relative to mild or ordinary COVID-19. Due to strong pairwise correlations, only five factors, including diagnostic delay (OR, 95% CI, p: 1.08, 1.02 to 1.17, 0.048), albumin (0.82, 0.75 to 0.91, <0.001), lactate dehydrogenase (1.56, 1.14 to 2.13, 0.011), white blood cell (1.27, 1.08 to 1.50, 0.004), and neutrophil (1.40, 1.16 to 1.70, <0.001), were retained for model construction and performance assessment. The nomogram model based on the five factors had good prediction capability and accuracy (C-index: 90.6%). Conclusions: Our findings provide evidence for the significant contribution of five independent factors to the risk of severe or critical COVID-19, and their prediction was reinforced in a nomogram model.

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出版当年[2020]版:
大类 | 2 区 医学
小类 | 1 区 老年医学 3 区 细胞生物学
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出版当年[2019]版:
Q1 GERIATRICS & GERONTOLOGY Q2 CELL BIOLOGY
最新[2023]版:
Q2 CELL BIOLOGY Q2 GERIATRICS & GERONTOLOGY

影响因子: 最新[2023版] 最新五年平均[2021-2025] 出版当年[2019版] 出版当年五年平均[2015-2019] 出版前一年[2018版] 出版后一年[2020版]

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第一作者单位: [1]Department of Cardiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
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