Effectiveness of Artificial Intelligent Based mHealth System to Reduce ACS Patients Bleeding Events After PCI

NCT ID: NCT03738930

Last Updated: 2018-11-13

Study Results

Results pending

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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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

420 participants

Study Classification

INTERVENTIONAL

Study Start Date

2018-11-10

Study Completion Date

2020-01-01

Brief Summary

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The present study was designed to observe the effectiveness of artificial intelligent based mHealth system(Chronic disease management system) to reduce bleeding events in ACS patients undergoing PCI.

Detailed Description

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Conditions

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Acute Coronary Syndrome Percutaneous Coronary Intervention Bleeding

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

PREVENTION

Blinding Strategy

NONE

Study Groups

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normal follow-up group

normal follow-up in ACS patients after PCI

Group Type NO_INTERVENTION

No interventions assigned to this group

AI based mHealth system follow-up group

AI based mHealth system follow-up in ACS patients after PCI. ACS patients in this group will receive message to take more notice to bleeding events.

Group Type EXPERIMENTAL

AI based mHealth system

Intervention Type BEHAVIORAL

AI based mHealth system is used to deliver self-management contral message and health education message to make patients take notice of bleeding events after PCI.

Interventions

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AI based mHealth system

AI based mHealth system is used to deliver self-management contral message and health education message to make patients take notice of bleeding events after PCI.

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

age≄18 years, male or female; confirmed acute coronary syndrome patients; undergo percutaneous coronary intervention (PCI) treatment; good command of smart phones agree to participate in this clinical study and sign a written consent form.

Exclusion Criteria

ACS admission deemed secondary to other cause such as traffic accidents, trauma, severe upper gastrointestinal bleeding, surgery, or procedure; patients who are not intend to attend 1 year of follow-up study or investigators find that patients are not able to comply with the study's requirements; pregnant women or lactating women; investigators consider patients who were not suitable for participation with other reasons
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Chinese PLA General Hospital

OTHER

Sponsor Role lead

Responsible Party

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Yun Dai Chen

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Yundai Chen, Master

Role: PRINCIPAL_INVESTIGATOR

The General Hospital of PLA

Locations

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The General Hospital of PLA

Beijing, Beijing Municipality, China

Site Status RECRUITING

Countries

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China

Central Contacts

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Dandan Li, Master

Role: CONTACT

+86 15711017209

Yundai Chen, Master

Role: CONTACT

Facility Contacts

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Dandan Li, Master

Role: primary

+86 15711017209

Other Identifiers

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AI-mHealth-pilot

Identifier Type: -

Identifier Source: org_study_id

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