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Clinical Trial Details — Status: Not yet recruiting

Administrative data

NCT number NCT05967546
Other study ID # XJTU1AF2023LSK-170
Secondary ID
Status Not yet recruiting
Phase
First received
Last updated
Start date December 30, 2024
Est. completion date December 31, 2028

Study information

Verified date April 2024
Source First Affiliated Hospital Xi'an Jiaotong University
Contact Guoliang Li, M.D.
Phone +8613759982523
Email liguoliang_med@163.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

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


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.


Recruitment information / eligibility

Status Not yet recruiting
Enrollment 4000
Est. completion date December 31, 2028
Est. primary completion date August 31, 2028
Accepts healthy volunteers No
Gender All
Age group 3 Years and older
Eligibility 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.

Study Design


Related Conditions & MeSH terms


Intervention

Other:
Observational
No interventions will be given to patients.

Locations

Country Name City State
China First Affiliated Hospital of Xi'an Jiantong University Xi'an Shaanxi

Sponsors (4)

Lead Sponsor Collaborator
First Affiliated Hospital Xi'an Jiaotong University 521 Hospital of NORINCO Group, Shaanxi Provincial People's Hospital, Xiangyang Central Hospital

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary 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 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.
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