Morality, Predictive Model, Risk Factor, Sepsis
Conditions
Brief summary
The purpose of this study was to investigate the risk factors for mortality of sepsis and to create mathematical models to predict the survival rate based on electronic health records that extracted from hospital information system. More than 1000 records should be collected and used to data analysis. Univariate and multivariable logistic regression model were applied to risk factors analysis for the outcome, and machine learn algorithms were employed to generate predictive models for the outcome.
Interventions
regular medical treatment
Sponsors
Department of Emergence, The First Hospital Affiliated to South China University, Hengyang, Hunan, China.
Department of Integrative Medicine, Huashan Hospital of Fudan University, Shanghai, China
Department of Biomedical Informatics and Statistics, Insitute of Integrative Medicine, Fudan University, Shanghai, China
Department of emergence, Hunan people's hospital, Changhai, Hunan, China
Department of emergence, The hospital affiliated to Jining medical college, Jining, Shandong, China
Department of emergence, Huaihua people's hospital, Huaihua, Hunan, China
Shanghai Tongji Hospital, Tongji University School of Medicine
Study design
Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
14 Years to 99 Years
Healthy volunteers
No
Inclusion criteria
* all records with sepsis in emergence department of hospitals
Exclusion criteria
* subjects with major missing data
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| mortality of sepsis | 4 weeks | mortality of sepsis |
Countries
China
Outcome results
None listed