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

November 29, 2022 updated by: Songqiao Liu, Southeast University, China
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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

Build the early warning system.

Study Type

Interventional

Enrollment (Anticipated)

1000

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Jiangsu
      • Nanjing, Jiangsu, China, 210009
        • Recruiting
        • Zhongda Hospital, Southeast University
        • Contact:
        • Contact:
          • Haibo Qiu, Doctor
          • Phone Number: 025-83262553

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 80 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Non-Randomized
  • Interventional Model: Sequential Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: AI group
patients evaluated by early warning platform
Device: early warning platform
High risk inpatients will be evaluated by early warning platform
No Intervention: usual care group
patients not evaluated by early warning platform

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
28-day all cause mortality
Time Frame: 28 days
28-day all cause mortality
28 days

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Hospital mortality
Time Frame: through study completion, an average of 1 month
Hospital mortality
through study completion, an average of 1 month

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Southeast University, China

Investigators

  • Principal Investigator: Songqiao Liu, PhD., Zhongda Hospital, Southeast University, China

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 1, 2022

Primary Completion (Anticipated)

June 1, 2023

Study Completion (Anticipated)

December 1, 2023

Study Registration Dates

First Submitted

June 4, 2022

First Submitted That Met QC Criteria

June 4, 2022

First Posted (Actual)

June 8, 2022

Study Record Updates

Last Update Posted (Actual)

December 1, 2022

Last Update Submitted That Met QC Criteria

November 29, 2022

Last Verified

November 1, 2022

More Information

Terms related to this study

Other Study ID Numbers

  • 2021ZDSYLL346-P01

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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