Clinical trial NCT04061434: ECG Algorithms for CRT Response Evaluation
Official title: Evaluation of the Effectiveness of CRT Therapy Based on the Record From an Implantable Device
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: ECG Monitoring
Keywords: Cardiac Resynchronization Therapy
ECG Algorithms
Machine based learning
Lead sponsor: Medical University of Warsaw
Sponsor class: OTHER
Collaborators: name: National Center for Research and Development, Poland
First posted: 2019-08-19
Enrollment: 547
Sex: ALL
Minimum age (years): 18
Maximum age (years): 100
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
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.

Brief 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. 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.

Eligibility criteria: Inclusion Criteria:

* 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

Exclusion Criteria:

* Patient's lack of consent
* Pacemaker dependency with patient's own rhythm insufficient for appropriate perfusion of central nervous system

Primary outcomes:
measure: Number of correctly assessed ECG signals by the automatic recognition of resynchronization in CRT-mediated therapy.
timeFrame: 14 months
measure: Correctly recognized ECG signals after adding each cycle of 20 new ECG recordings from patients with electrical heart function disturbances.
timeFrame: 7 months
Secondary outcomes:
measure: Number of registered ECG signals from patients holding a CIED.
timeFrame: 14 months
Other outcomes:
Locations:
city: Warsaw
country: Poland
facility: 1st Department of Cariology of Medcial University of Warsaw
state: Mazowieckie
Study officials:
References: