Machine Learning-based Early Clinical Warning of High-risk Patients

Risk Reduction Clinical Trial

Official title:

Machine Learning-based Early Clinical Warning of High-risk Patients

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05410171
• Other study ID #: 2021ZDSYLL346-P01
• Status: Recruiting
• Phase: N/A
• Start date: June 1, 2022
• Est. completion date: December 1, 2023

Study information

• Verified date: November 2022
• Source: Southeast University, China
• Contact: Changde Wu
• Phone: 086-02583262550
• Email: liusongqiao[@]ymail.com
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Through the early warning platform for inpatients established by our hospital, the various indicators of patients collected in real time are carried out for automated intelligent evaluation and analysis, early warning of high-risk patients to assess the impact on patient prognosis and the impact on the occurrence of adverse events in inpatients.

Description:

Build the early warning system.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1000
• Est. completion date: December 1, 2023
• Est. primary completion date: June 1, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

Inclusion Criteria:

1. Patients who use ECG monitoring

2. Age = 18 years old

3. Understand and sign an informed consent form

Exclusion Criteria:

• Pregnancy or lactation

Related Conditions & MeSH terms

• High-risk Patients
• Machine Learning
• Risk Reduction

Intervention

Device:
• early warning platform
High risk inpatients will be evaluated by early warning platform

Locations

Country	Name	City	State
China	Zhongda Hospital, Southeast University	Nanjing	Jiangsu

Sponsors (1)

Lead Sponsor	Collaborator
Southeast University, China

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	28-day all cause mortality	28-day all cause mortality	28 days
Secondary	Hospital mortality	Hospital mortality	through study completion, an average of 1 month