Development of a Predictive Model for Mortality in Hospitalized Patients With COVID-19.
Disaster Med Public Health Prep
; 16(4): 1398-1406, 2022 08.
Article
in English
| MEDLINE | ID: covidwho-1014945
ABSTRACT
INTRODUCTION:
Early identification of patients with novel corona virus disease 2019 (COVID-19) who may be at high mortality risk is of great importance.METHODS:
In this retrospective study, we included all patients with COVID-19 at Huanggang Central Hospital from January 23 to March 5, 2020. Data on clinical characteristics and outcomes were compared between survivors and nonsurvivors. Univariable and multivariable logistic regression were used to explore risk factors associated with in-hospital death. A nomogram was established based on the risk factors selected by multivariable analysis.RESULTS:
A total of 150 patients were enrolled, including 31 nonsurvivors and 119 survivors. The multivariable logistic analysis indicated that increasing the odds of in-hospital death associated with higher Sequential Organ Failure Assessment score (odds ratio [OR], 3.077; 95% confidence interval [CI] 1.848-5.122; P < 0.001), diabetes (OR, 10.474; 95% CI 1.554-70.617; P = 0.016), and lactate dehydrogenase greater than 245 U/L (OR, 13.169; 95% CI 2.934-59.105; P = 0.001) on admission. A nomogram was established based on the results of the multivariable analysis. The AUC of the nomogram was 0.970 (95% CI 0.947-0.992), showing good accuracy in predicting the risk of in-hospital death.CONCLUSIONS:
This finding would facilitate the early identification of patients with COVID-19 who have a high-risk for fatal outcome.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
COVID-19
Type of study:
Observational study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Disaster Med Public Health Prep
Journal subject:
Public Health
Year:
2022
Document Type:
Article
Affiliation country:
Dmp.2021.8
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