Feasibility of AI-based Heart Function Prediction Model U... | NCT04996381

Studies
Feasibility of AI-based Heart Function Prediction Model Using CXR

NCT04996381

Sponsor

Yonsei University

Status

Completed

Last Update Posted

Sep 14, 2022Actual

Enrollment

505Actual

Phase

Not provided

Conditions

Chest X-ray for Clinical Evaluation

Interventions

Scanning Chest X-rays and performing AI algorithms on images

Countries

South Korea

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Sep 2022

Overall Recruitment Status or Expanded Access Status

Completed

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Mar 1, 2022Actual

Primary Completion Date

Jun 30, 2022Actual

Completion Date

Sep 1, 2022Actual

First Submitted Date

Aug 4, 2021

First Submission Date that Met QC Criteria

Aug 4, 2021

First Posted Date

Aug 9, 2021Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Sep 12, 2022

Last Update Posted Date

Sep 14, 2022Actual

Oversight Module

Has Data Monitoring Committee (DMC)

Yes

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief Summary

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

Detailed Description

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

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

505Actual

Arms/Interventions Module

Arm Groups

Not provided

Interventions

Name	Type	Description	Arm Group Labels	Other Names
Scanning Chest X-rays and performing AI algorithms on images	Diagnostic Test	Chest X-Rays; AI CNNs; Results

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Left Ventricular Ejection Fraction < 40%	Evaluate the performance of chest X-ray based artificial intelligence algorithms to identify individuals with reduced ejection fraction (<40%)	Within two weeks of chest X-ray

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

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

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

20 Years

Maximum Age

90 Years

Standard Ages

AdultOlder Adult

Study Population

Patients undergoing a transthoracic echocardiogram will be enrolled.

Sampling Method

Non-Probability Sample

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Name	Affiliation	Role
In Hyun Jung, MD, PhD	Yongin Severance Hospital, Yonsei University College of Medicine	Study Chair

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Yongin Severance Hospital		Yongin	Giheung-gu	16995	South Korea