Status:

UNKNOWN

A Machine Learning Predictive Model for Sepsis

Lead Sponsor:

Xinhua Hospital, Shanghai Jiao Tong University School of Medicine

Conditions:

Sepsis

Eligibility:

All Genders

1-18 years

Brief Summary

Timely and accurately predicting the occurrence of sepsis and actively intervening in treatment may effectively improve the survival and cure rate of patients with sepsis. Using machine learning and ...

Detailed Description

Introduction:Timely and accurately predicting the occurrence of sepsis and actively intervening in treatment may effectively improve the survival and cure rate of patients with sepsis. There have been...

Eligibility Criteria

Inclusion

  • diagnosed with "infection", "septic shock" or "sepsis" or "septicemia"

Exclusion

  • Acute upper respiratory tract infection
  • Newborns

Key Trial Info

Start Date :

April 1 2019

Trial Type :

OBSERVATIONAL

Allocation :

ESTIMATED

End Date :

April 1 2021

Estimated Enrollment :

4500 Patients enrolled

Trial Details

Trial ID

NCT04771429

Start Date

April 1 2019

End Date

April 1 2021

Last Update

February 25 2021

Active Locations (1)

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Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

Shanghai, Yangpu, China, 200092