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Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China.
Chen, Xin; Peng, Feng; Zhou, Xiaoni; Zhu, Jiang; Chen, Xin; Gong, Yingying; Shupeng, Wang; Niu, Wenquan.
  • Chen X; Department of Cardiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Peng F; Department of Cardiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Zhou X; Department of Pulmonary Disease, The Third People's Hospital of Yichang, Yichang, Hubei, China.
  • Zhu J; Department of Cardiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Chen X; Department of Cardiology Nursing Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Gong Y; Department of Cardiology Nursing Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Shupeng W; Department of Cardiology Nursing Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
  • Niu W; Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China.
Aging (Albany NY) ; 13(2): 1608-1619, 2020 12 09.
Article in English | MEDLINE | ID: covidwho-977832
ABSTRACT

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 COVID-19. 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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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biomarkers / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Long Covid Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: English Journal: Aging (Albany NY) Journal subject: Geriatrics Year: 2020 Document Type: Article Affiliation country: Aging.202261

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biomarkers / COVID-19 Type of study: Diagnostic study / Prognostic study Topics: Long Covid Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: English Journal: Aging (Albany NY) Journal subject: Geriatrics Year: 2020 Document Type: Article Affiliation country: Aging.202261