ECG MonitoringOVERCOMENCT04061434
ECG Algorithms for CRT Response Evaluation
An observational study of ECG Monitoring, run by Medical University of Warsaw at 1 site in Poland.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 to 100 years
- Conditions the study is for
- ECG Monitoring
- How many people
- 547 participants
- Where
- 1 sitePoland
- Study dates
- 1 Mar 2019to 30 Jul 2020
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 100 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: 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.
Who may be able to join
- State after CRT implantation with cardiac defibrillation function (CRT-D)
- State after CRT implantation with pacing function (CRT-P)
- State after implantation of cardiac pacemaker
- State after ICD implantation with indications for periodic heart stimulation
- Signed written informed consent
Who cannot join
- Patient's lack of consent
- Pacemaker dependency with patient's own rhythm insufficient for appropriate perfusion of central nervous system
Trial locations and contacts
1 site in 1 country.
Poland1 site
1st Department of Cariology of Medcial University of Warsaw
Warsaw, Masovian Voivodeship, 02-097
About this study
Official title: Evaluation of the Effectiveness of CRT Therapy Based on the Record From an Implantable Device
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.
Read the detailed description
The study is an investigator-initiated, single centre, prospective observational trial. The study will be carried out in university hospital on electrocardiology ward. The study will consist of two independent groups of patients whose ECG will be collected using the standard 12-lead ECG or 24-hour Holter monitoring. The study groups will be as follows: cardiac resynchronization therapy (CRT) recipients with pacemaker or defibrillation function, patients after cardiac implantable electronic devices (CIED) such as : cardiac pacemaker, patients with implantable cardioverter defibrillator (ICD) with indications for periodic heart stimulation. Approval for all study groups was obtained from institutional review board. In patients with already implanted device signal will be recorded in pacing mode and standby mode. What is more, in patients with CRT-D/CRT-P signal will be registered with different configurations of stimulation (no stimulation, right ventricle pacing, left ventricle pacing, biventricular pacing) and by stimulation different regions of left ventricle. Patients medical history will be acquired : comorbidities, qualification for device implantation, and other examinations at that time. In selected patients with typically good response for CRT, ECG signal will be registered with Holter method. Based on collected ECG, the correlation between clinical data parameters predicting good therapy response will be determined. ECG platform. The analysing system for arrhythmia detection consists of cloud-based software platform. The captured electrocardiographic signal uploaded to the platform is analysed using deep neural networks algorithms. The software allows the ECG standard report visualisation of signal and analysis of acquired data in terms of CRT sufficiency. The platform is a medical device certified in the European Union.
- Conditions
- ECG Monitoring
- Keywords
- Cardiac Resynchronization Therapy, ECG Algorithms, Machine based learning
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Cardiac resynchronisation therapy recipients | Not described | |
| Other cardiac implantable electronic devices recipients | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: 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.
Measured: 7 months
Secondary outcomes (1)
Number of registered ECG signals from patients holding a CIED.
Creation of an database of ECG and Holter monitoring acquired signal from patients with cardiac implantable electronic devices (CIED).
Reaching more than 258 ECG recordings in the database to qualify and discriminate signal patterns that can be qualified as certain arrhythmia.
Measured: 14 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Aug 2019
- Study start1 Mar 2019
- Primary completion30 Jul 2020
- Study completion30 Jul 2020
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for ECG MonitoringStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 547 participants (actual)
Sponsor and investigators
- Lead sponsor
- Medical University of Warsaw
- Sponsor type
- University, hospital or other
- Collaborators
- National Center for Research and Development, Poland
- Responsible party
- Principal investigator, Marcin Grabowski, Medical University of Warsaw
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04061434
- Sponsor's protocol ID
- OVERCOME
- Acronym
- OVERCOME
- Status last verified
- Oct 2021
- First submitted
- 20 May 2019
- Last updated
- 6 Oct 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes
Study at a glance
From the registry record, last updated by the sponsor on 6 Oct 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of the Effectiveness of CRT Therapy Based on the Record From an Implantable Device
- ClinicalTrials.gov ID
- NCT04061434
- Acronym / sponsor ID
- OVERCOME / OVERCOME
- Conditions
- ECG Monitoring
- Keywords
- Cardiac Resynchronization Therapy, ECG Algorithms, Machine based learning
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 547 participants (actual)
- Lead sponsor
- Medical University of WarsawUniversity, hospital or other
- Collaborators
- National Center for Research and Development, Poland
- Study start
- 1 Mar 2019 (actual)
- Primary completion
- 30 Jul 2020 (actual)
- Study completion
- 30 Jul 2020 (actual)
- First posted
- 19 Aug 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
The study is an investigator-initiated, single centre, prospective observational trial. The study will be carried out in university hospital on electrocardiology ward. The study will consist of two independent groups of patients whose ECG will be collected using the standard 12-lead ECG or 24-hour Holter monitoring. The study groups will be as follows: cardiac resynchronization therapy (CRT) recipients with pacemaker or defibrillation function, patients after cardiac implantable electronic devices (CIED) such as : cardiac pacemaker, patients with implantable cardioverter defibrillator (ICD) with indications for periodic heart stimulation. Approval for all study groups was obtained from institutional review board. In patients with already implanted device signal will be recorded in pacing mode and standby mode. What is more, in patients with CRT-D/CRT-P signal will be registered with different configurations of stimulation (no stimulation, right ventricle pacing, left ventricle pacing, biventricular pacing) and by stimulation different regions of left ventricle. Patients medical history will be acquired : comorbidities, qualification for device implantation, and other examinations at that time. In selected patients with typically good response for CRT, ECG signal will be registered with Holter method. Based on collected ECG, the correlation between clinical data parameters predicting good therapy response will be determined. ECG platform. The analysing system for arrhythmia detection consists of cloud-based software platform. The captured electrocardiographic signal uploaded to the platform is analysed using deep neural networks algorithms. The software allows the ECG standard report visualisation of signal and analysis of acquired data in terms of CRT sufficiency. The platform is a medical device certified in the European Union.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Cardiac resynchronisation therapy recipients | – | – |
| Other cardiac implantable electronic devices recipients | – | – |
Who may qualify
- Ages
- 18 to 100 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- 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.
Key inclusion criteria (5 listed)
- State after CRT implantation with cardiac defibrillation function (CRT-D)
- State after CRT implantation with pacing function (CRT-P)
- State after implantation of cardiac pacemaker
- State after ICD implantation with indications for periodic heart stimulation
- Signed written informed consent
Key exclusion criteria (2 listed)
- Patient's lack of consent
- Pacemaker dependency with patient's own rhythm insufficient for appropriate perfusion of central nervous system
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Number of correctly assessed ECG signals by the automatic recognition of resynchronization in CRT-mediated therapy.
Time frame: 14 months
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
Correctly recognized ECG signals after adding each cycle of 20 new ECG recordings from patients with electrical heart function disturbances.
Time frame: 7 months
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.
1 secondary outcome
Number of registered ECG signals from patients holding a CIED.
Time frame: 14 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Oct 2021.
- Individual participant dataSharing planned: Yes
Related trials for ECG Monitoring
RecruitingObservational study
Clinical Performance and Usability of the Heart Rate and Impedance Respiration Monitor Cable
Monitoring, ECG
Not yet recruiting
Head-to-Head (H2H) Comparison of Ambulatory Cardiac ECG Monitors in Japan
Atrial Fibrillation (AF), Atrial Flutter
Recruiting
Smart Textile ECG Monitoring
Cardiac Arrhythmia
Recruiting
Hativ® ELectrocardiogram Monitoring on Patients With Suspected Arrhythmia
Arrhythmia
Recruiting
Diagnostic Efficacy of Connected WAtch ECG Versus External Holter ECG
Heart Disease
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of ECG Monitoring, run by Medical University of Warsaw at 1 site in Poland.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 6 Oct 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Poland. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of correctly assessed ECG signals by the automatic recognition of resynchronization in CRT-mediated therapy. (time frame: 14 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Oct 2021.