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