Atrial Fibrillation Detecting Software Gung Atrial Fibrillation Detecting Software

NCT05872516 | Completed

• 1 other identifier: 202200717A3
• Study Type: interventional
• Target: 788
• Locations: 1 country
• Sites: 1

Brief Summary

Chang Gung Atrial Fibrillation Detection Software is an artificial intelligence electrocardiogram signal analysis software that detects whether a patient has atrial fibrillation by static 12-lead ECG signals. This study is a non-inferiority test based on the control group. The main purpose is to verify whether Chang Gung atrial fibrillation detection software can correctly identify atrial fibrillation in patients with atrial fibrillation, and can be used to provide a reference for doctors to detect atrial fibrillation.

Conditions

Atrial Fibrillation

Keywords

artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Sensitivity

  The rate of test results that correctly indicate the presence.

  baseline

Secondary Outcomes (7)

• Specificity

  baseline

• Accuracy

  baseline

• Area Under the receiver operating characteristic Curve

  baseline

• Positive predictive value

  baseline

• Negative predictive value

  baseline

Study Arms (1)

Software diagnosis

EXPERIMENTAL

Software diagnosis with gold standard of 3 doctors' consensus.

Device: Chang Gung Atrial Fibrillation Detecting Software

Interventions

Chang Gung Atrial Fibrillation Detecting Software DEVICE

This software is expected to be used in clinical testing to interpret the static 12-lead ECG of adults who are over 20 years old and suspected of having atrial fibrillation, detect whether there is a signal of atrial fibrillation, and output the results for clinicians Near-instant auxiliary diagnostic use.

Software diagnosis

Eligibility Criteria

• Age: 20 Years - 100 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Equal or greater than twenty years old
• Static 12-lead electrocardiogram of General Electric MUSE XML format file.
• The data comes from the static 12-lead electrocardiogram device of General Electric (model MAC5500).
• The electrocardiogram signal is 500 Hz.
• The Alternating current (AC) filter of the electrocardiogram signal is 60 Hz.

You may not qualify if:

• Cases used in the model development process.
• Lacks any electrode.
• Contain any electrode lacks a segment.
• Misplaced leads

Sponsors & Collaborators

• Chang Gung Memorial Hospital: lead

Study Sites (1)

Chang Gung memorial hospital

Taoyuan, 333, Taiwan

Location

Related Publications (4)

• Mant J, Fitzmaurice DA, Hobbs FD, Jowett S, Murray ET, Holder R, Davies M, Lip GY. Accuracy of diagnosing atrial fibrillation on electrocardiogram by primary care practitioners and interpretative diagnostic software: analysis of data from screening for atrial fibrillation in the elderly (SAFE) trial. BMJ. 2007 Aug 25;335(7616):380. doi: 10.1136/bmj.39227.551713.AE. Epub 2007 Jun 29.

  PMID: 17604299 BACKGROUND

• US Preventive Services Task Force; Curry SJ, Krist AH, Owens DK, Barry MJ, Caughey AB, Davidson KW, Doubeni CA, Epling JW Jr, Kemper AR, Kubik M, Landefeld CS, Mangione CM, Silverstein M, Simon MA, Tseng CW, Wong JB. Screening for Atrial Fibrillation With Electrocardiography: US Preventive Services Task Force Recommendation Statement. JAMA. 2018 Aug 7;320(5):478-484. doi: 10.1001/jama.2018.10321.

  PMID: 30088016 BACKGROUND

• Wong KC, Klimis H, Lowres N, von Huben A, Marschner S, Chow CK. Diagnostic accuracy of handheld electrocardiogram devices in detecting atrial fibrillation in adults in community versus hospital settings: a systematic review and meta-analysis. Heart. 2020 Aug;106(16):1211-1217. doi: 10.1136/heartjnl-2020-316611. Epub 2020 May 11.

  PMID: 32393588 BACKGROUND

• Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomstrom-Lundqvist C, Boriani G, Castella M, Dan GA, Dilaveris PE, Fauchier L, Filippatos G, Kalman JM, La Meir M, Lane DA, Lebeau JP, Lettino M, Lip GYH, Pinto FJ, Thomas GN, Valgimigli M, Van Gelder IC, Van Putte BP, Watkins CL; ESC Scientific Document Group. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS): The Task Force for the diagnosis and management of atrial fibrillation of the European Society of Cardiology (ESC) Developed with the special contribution of the European Heart Rhythm Association (EHRA) of the ESC. Eur Heart J. 2021 Feb 1;42(5):373-498. doi: 10.1093/eurheartj/ehaa612. No abstract available.

  PMID: 32860505 BACKGROUND

MeSH Terms

Conditions

Atrial Fibrillation

Condition Hierarchy (Ancestors)

Arrhythmias, Cardiac; Heart Diseases; Cardiovascular Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Chang-Fu Kuo, MD/Ph.D

  Associate Professor and Director Division of Rheumatology

  STUDY CHAIR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 4, 2023
• First Posted: May 24, 2023
• Study Start: July 11, 2022
• Primary Completion: February 8, 2023
• Study Completion: April 10, 2023
• Last Updated: May 24, 2023

Record last verified: 2023-04

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)