Machine Learning-based Early Clinical Warning of High-risk Patients
NCT ID: NCT05410171
Last Updated: 2022-12-01
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
1000 participants
INTERVENTIONAL
2022-06-01
2023-12-01
Brief Summary
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Detailed Description
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Conditions
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Study Design
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NON_RANDOMIZED
SEQUENTIAL
HEALTH_SERVICES_RESEARCH
NONE
Study Groups
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AI group
patients evaluated by early warning platform
early warning platform
High risk inpatients will be evaluated by early warning platform
usual care group
patients not evaluated by early warning platform
No interventions assigned to this group
Interventions
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early warning platform
High risk inpatients will be evaluated by early warning platform
Eligibility Criteria
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Inclusion Criteria
2. Age ≥ 18 years old
3. Understand and sign an informed consent form
Exclusion Criteria
18 Years
80 Years
ALL
No
Sponsors
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Southeast University, China
OTHER
Responsible Party
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Songqiao Liu
Head of Information Division
Principal Investigators
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Songqiao Liu, PhD.
Role: PRINCIPAL_INVESTIGATOR
Zhongda Hospital, Southeast University, China
Locations
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Zhongda Hospital, Southeast University
Nanjing, Jiangsu, China
Countries
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Central Contacts
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Facility Contacts
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Haibo Qiu, Doctor
Role: backup
Other Identifiers
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2021ZDSYLL346-P01
Identifier Type: -
Identifier Source: org_study_id
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