Feasibility of AI-based Heart Function Prediction Model Using CXR

NCT ID: NCT04996381

Last Updated: 2022-09-14

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

COMPLETED

Total Enrollment

505 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-03-01

Study Completion Date

2022-09-01

Brief Summary

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The investigators will develop an artificial intelligence model to predict left ventricular ejection fraction using chest radiographic images and transthoracic echocardiography data.

Detailed Description

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Echocardiography should be considered at an early stage in patients who have first developed heart failure or who do not have information about heart function, but the examination may be delayed due to lack of time and manpower in the actual medical field.

Primary Objective: Use chest radiographs to predict the left ventricular ejection fraction

Conditions

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Chest X-ray for Clinical Evaluation

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Interventions

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Scanning Chest X-rays and performing AI algorithms on images

Chest X-Rays; AI CNNs; Results

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* Adults who are 20 years and older
* Patient who visited the emergency room or outpatient clinic due to dyspnea and chest pain

Exclusion Criteria

* Patient refusal
* Uncertain radiographs or transthoracic echocardiography
* Uncertain tests results
Minimum Eligible Age

20 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Yonsei University

OTHER

Sponsor Role lead

Responsible Party

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SungA Bae

MD. PhD.

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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In Hyun Jung, MD, PhD

Role: STUDY_CHAIR

Yongin Severance Hospital, Yonsei University College of Medicine

Locations

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Yongin Severance Hospital

Yŏngin, Giheung-gu, South Korea

Site Status

Countries

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South Korea

Other Identifiers

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YonseiU

Identifier Type: -

Identifier Source: org_study_id

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