Mathematical Modeling and Risk Factor Analysis for Mortality of Sepsis

NCT03883061 | Unknown

• 1 other identifier: 20190319
• Study Type: observational
• Target: 2,000
• Locations: 1 country
• Sites: 1

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.

Conditions

Morality; Risk Factor, Sepsis; Predictive Model

Outcome Measures

Primary Outcomes (1)

• mortality of sepsis

  mortality of sepsis

  4 weeks

Study Arms (1)

mortality of sepsis

the study sample would be extracted from electronic health records in emergence departments. risk factor analysis and mathematical modeling would be performed to evaluate the significant and independent risk factors and predictive models.

Other: regular medical treatment

Interventions

regular medical treatment OTHER

regular medical treatment

mortality of sepsis

Eligibility Criteria

• Age: 14 Years - 99 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

all patients with sepsis in emergence department of hospitals

You may qualify if:

• all records with sepsis in emergence department of hospitals

You may not qualify if:

• subjects with major missing data

Sponsors & Collaborators

• Shanghai Tongji Hospital, Tongji University School of Medicine: lead
• Department of Emergence, The First Hospital Affiliated to South China University, Hengyang, Hunan, China.: collaborator
• Department of Integrative Medicine, Huashan Hospital of Fudan University, Shanghai, China: collaborator
• Department of Biomedical Informatics and Statistics, Insitute of Integrative Medicine, Fudan University, Shanghai, China: collaborator
• Department of emergence, Hunan people's hospital, Changhai, Hunan, China: collaborator
• Department of emergence, The hospital affiliated to Jining medical college, Jining, Shandong, China: collaborator
• Department of emergence, Huaihua people's hospital, Huaihua, Hunan, China: collaborator

Study Sites (1)

Zihui Tang

Shanghai, China

RECRUITING

Related Publications (1)

• Lu Y, Tang ZH, Zeng F, Li Y, Zhou L. The association and predictive value analysis of metabolic syndrome combined with resting heart rate on cardiovascular autonomic neuropathy in the general Chinese population. Diabetol Metab Syndr. 2013 Nov 17;5(1):73. doi: 10.1186/1758-5996-5-73.

  PMID: 24238358 BACKGROUND

MeSH Terms

Conditions

Sepsis

Condition Hierarchy (Ancestors)

Infections; Systemic Inflammatory Response Syndrome; Inflammation; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: CROSS SECTIONAL
• Target Duration: 1 Month
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: March 19, 2019
• First Posted: March 20, 2019
• Study Start: January 1, 2017
• Primary Completion: March 1, 2019
• Study Completion: December 31, 2021
• Last Updated: January 6, 2021

Record last verified: 2021-01

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)