Deep Learning for Intelligent Identification of Arrhythmias | NCT05967546

Studies
Deep Learning for Intelligent Identification of Arrhythmias

NCT05967546

Sponsor

First Affiliated Hospital Xi'an Jiaotong University

Status

Not yet recruiting

Last Update Posted

Apr 4, 2024Actual

Enrollment

4,000Estimated

Phase

Not provided

Conditions

Arrhythmia

Interventions

Observational

Countries

China

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

Apr 2024

Overall Recruitment Status or Expanded Access Status

Not yet recruiting

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Dec 30, 2024Estimated

Primary Completion Date

Aug 31, 2028Estimated

Completion Date

Dec 31, 2028Estimated

First Submitted Date

Jul 6, 2023

First Submission Date that Met QC Criteria

Jul 21, 2023

First Posted Date

Aug 1, 2023Actual

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

Apr 2, 2024

Last Update Posted Date

Apr 4, 2024Actual

Name	Class
521 Hospital of NORINCO Group	OTHER
Shaanxi Provincial People's Hospital	OTHER
Xiangyang Central Hospital	OTHER

Oversight Module

Has Data Monitoring Committee (DMC)

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

This study aims to design and train a deep learning model for the diagnosis of different arrhythmias.

Detailed Description

This study aims to retrospectively and prospectively collect routine clinical data such as electrocardiograms from patients with arrhythmias who meet the inclusion and exclusion criteria. Then we will design and train a deep learning model to analyse the electrocardiographic features of the arrhythmias, and identify the types of arrhythmias and evaluate the value of the model for the diagnosis of different arrhythmias.

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

4,000Estimated

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
Experimental Group		ECG data and clinical data from this group of arrhythmia patients will be used to build a deep learning model.	Other: Observational

Interventions

Name	Type	Description	Arm Group Labels	Other Names
Observational	Other	No interventions will be given to patients.	Experimental Group

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
A deep learning model designed to intelligently identify the types of arrhythmia.	The model is trained on the training set, the best model and hyperparameters are selected through the verification set, and finally the model results are tested on the test set.	1 day after the enrollment.

Secondary Outcomes

Measure	Description	Time Frame
The sensitivity, specificity and accuracy of the deep learning model	The sensitivity, specificity and accuracy of a deep learning model designed were evaluated by intracardiac electrophysiological examination results to identify patients with arrhythmia from various centers.	1 day after the enrollment.

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

For retrospective study: 1.Patients with arrhythmia diagnosed by routine surface 12-lead electrocardiogram or Holter; 2.The type of arrhythmia is diagnosed by intracardiac electrophysiological examination.
For prospective study: 1.Patients with arrhythmia diagnosed by routine surface 12-lead electrocardiogram or Holter; 2.Intracardiac electrophysiological examination is planned.

Exclusion Criteria:

Lack of routine surface 12-lead electrocardiogram or holter data;
Lack of intracardiac electrophysiological examination;
Patients refused to sign informed consent and refused to participate in the study.

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

3 Years

Maximum Age

Not provided

Standard Ages

ChildAdultOlder Adult

Study Population

Patients diagnosed with arrhythmia by twelve-lead electrocardiogram or Holter.

Sampling Method

Non-Probability Sample

Contacts/Locations Module

Central Contacts

Name	Role	Phone	Extension	Email
Guoliang Li, M.D.	Contact	+8613759982523		liguoliang_med@163.com
Chaofeng Sun, M.D.	Contact			cfsun1@mail.xjtu.edu.cn

Overall Officials

Name	Affiliation	Role
Guoliang Li, M.D.	First Affiliated Hospital Xi'an Jiaotong University	Principal Investigator

Locations

Facility	Status	City	State	ZIP	Country	Contacts
First Affiliated Hospital of Xi'an Jiantong University		Xi'an	Shaanxi	710061	China

Condition Browse Module

MeSH Terms

ID	Term
D001145	Arrhythmias, Cardiac

Ancestor Terms

ID	Term
D006331	Heart Diseases
D002318	Cardiovascular Diseases
D010335	Pathologic Processes
D013568	Pathological Conditions, Signs and Symptoms

Browse Leaves

Not provided

Browse Branches

Not provided

Intervention Browse Module

MeSH Terms

ID	Term
D057832	Watchful Waiting

Ancestor Terms

ID	Term
D017063	Outcome Assessment, Health Care
D010043	Outcome and Process Assessment, Health Care
D011787	Quality of Health Care
D006298	Health Services Administration

Browse Leaves

Not provided

Browse Branches

Not provided