Mathematical Modeling and Risk Factor Analysis for Mortality of Sepsis

Overview

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.

Full Title of Study: “Mathematical Modeling and Risk Factor Analysis for Mortality of Sepsis Based on Real World Data in China”

Study Type

  • Study Type: Observational [Patient Registry]
  • Study Design
    • Time Perspective: Cross-Sectional
  • Study Primary Completion Date: March 1, 2019

Interventions

  • Other: regular medical treatment
    • regular medical treatment

Arms, Groups and Cohorts

  • 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.

Clinical Trial Outcome Measures

Primary Measures

  • mortality of sepsis
    • Time Frame: 4 weeks
    • mortality of sepsis

Participating in This Clinical Trial

Inclusion Criteria

  • all records with sepsis in emergence department of hospitals Exclusion Criteria:

  • subjects with major missing data

Gender Eligibility: All

Minimum Age: 14 Years

Maximum Age: 99 Years

Are Healthy Volunteers Accepted: No

Investigator Details

  • Lead Sponsor
    • Shanghai Tongji Hospital, Tongji University School of Medicine
  • Collaborator
    • Department of Emergence, The First Hospital Affiliated to South China University, Hengyang, Hunan, China.
  • Provider of Information About this Clinical Study
    • Principal Investigator: Zihui Tang, Associate Professor – Huashan Hospital

References

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.

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