NCT04061434|Completed
ECG Algorithms for CRT Response Evaluation
OVERCOME
Evaluation of the Effectiveness of CRT Therapy Based on the Record From an Implantable Device
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OVERCOME
Evaluation of the Effectiveness of CRT Therapy Based on the Record From an Implantable Device
Sponsor study identifier
observational
547
1 country
1
Study Start
March 1, 2019
Actual (reported)Primary Completion
July 30, 2020
Actual (reported)Study Completion
July 30, 2020
Actual (reported)Cardiovascular diseases (CVD) are associated with high healthcare costs,as well as are a leading cause of mortality and hospitalizations. One of CVDs is a heart failure which may be associated with dyssynchrony of contraction of right and left ventricle. Chance for group of patients whose pharmacotherapy is not enough is cardiac resynchronisation therapy (CRT). Effectiveness of CRT has been proven in various multicenter clinical studies. The challenge limiting CRT usage is it relative low effectiveness - with significant group of patients that do not respond to this method of therapy. The device itself does not always show the true level of stimulation during interrogation; then invalid functioning is often not detected, which presents a real danger to patient's health and life. The main challenge for today's researchers is to develop new technologies, which may help to improve diagnosis of CVD, thereby reducing healthcare costs and quality of patients' lives. Smart computed systems of ECG analysis and interpretation offer new capabilities for the diagnosis and management of patients with CRT. Several reports with intelligent machine-based learning algorithms have been published, in which achieved very positive results in detecting various ECG abnormalities. Aim of our study is to show utility of ECG interpretation software in patients with CRT to assess the CRT response using Cardiomatics system.
Registry-reported information. Elapsed time and enrollment totals alone do not measure study progress or recruitment pace.
July 30, 2020
Actual (reported)Click on a node to explore related trials.
Dates and qualifiers reported by the registry. Estimated dates do not confirm that a milestone has occurred.
March 1, 2019
Actual (reported)May 20, 2019
Actual (reported)August 19, 2019
Actual (reported)July 30, 2020
Actual (reported)July 30, 2020
Actual (reported)Number of correctly assessed ECG signals by the automatic recognition of resynchronization in CRT-mediated therapy.
Evaluating the effectiveness of CRT therapy based on the record from an implantable device Assessment of the rationale for the use of machine based learning algorithms in detecting ECG abnormalities to determine which clinical conditions have impact on long-term effectiveness of cardiac resynchronization therapy using both standard 12-lead ECG and 24-hour Holter monitoring . The study might identify which clinical parameters in patients with CRT indicate the most benefit and the least benefit from CRT. It is planned to reach 99% sensitivity of automatized recognizing resynchronization in CRT-mediated therapy
14 months
Correctly recognized ECG signals after adding each cycle of 20 new ECG recordings from patients with electrical heart function disturbances.
To achieve this goal we will collect representative base of ECG recordings containing both paced rhythm in subjects undergoing therapy and those in qualification process in order to use the software to predict CRT response. The final model assumes fully automatized diagnosis of CRT-therapy response based on machine learning. Using this feature in connection with new methods of digital signal processing will constantly increase system's efficacy measured by simultaneous achievement of high test specificity and sensitivity. Increase by 1% of test sensitivity withholding high specificity after adding each cycle of 20 new ECG recordings from patients with electrical heart function disturbances is planned.
7 months
Number of registered ECG signals from patients holding a CIED.
14 months
The study will be consisted of two independent patient groups: 250 patients treated with cardiac resynchronisation therapy (CRT) of whom 225 ECG signal will be acquired, and 15 24-hour Holter monitoring will be collected; 250 patients with other cardiac implantable electronic devices, of whom 225 ECG signal will be acquired and 15 24-hour Holter monitoring will be collected.
1st Department of Cariology of Medcial University of Warsaw
Warsaw, Masovian Voivodeship, 02-097, Poland
547 participants (actual enrollment reported by the registry).
First Submitted
May 20, 2019
First Posted
August 19, 2019
Study Start
March 1, 2019
Actual (reported)BDx 7 Day ECG Patch: Electrode Adhesion Clinical Study
Contact the study team to confirm eligibility.
Primary Completion
July 30, 2020
Actual (reported)Study Completion
July 30, 2020
Actual (reported)Last Updated
October 6, 2021
Record last verified: 2021-10
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Source: ClinicalTrials.gov.
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