Screening for Cardiac and Cardiac-associated Pathology Using Single-channel Electrocardiogram

April 13, 2026 updated by: I.M. Sechenov First Moscow State Medical University

Screening for Cardiac and Cardiac-associated Pathology Using Single-channel Electrocardiogram Analyzed With Machine Learning Models

It is a prospective, controlled, single-center, observational, non-randomized study. The study is planned to include at least 4000 patients 18 years old and older in the training sample and 1000 patients over 18 years old in the test sample (the total number of patients is at least 5000 people). Patients will be included in the study if they have undergone a full examination (laboratory, clinical and instrumental), allowing for the verification or exclusion of cardiac and cardiac-associated pathology in accordance with current recommendations. During the course of the study, the authors of the work do not interfere with the above-mentioned scope of the examination, which is carried out on patients in accordance with clinical guidelines. All patients included in the study will undergo ECG recording in standard lead I for 1 minute twice, followed by spectral analysis of the obtained data, which will be stored at the remote monitoring center of Sechenov University without being linked to the personal data of patients. A spectral analysis of the electrocardiogram will be performed using a continuous wavelet transform. The result of this study will be the identification of ECG parameters that will correlate with cardiac and cardiac-associated pathology

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Not yet recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Detailed Description

The aim of the study is to develop, evaluate the diagnostic efficacy, and pilot a screening method for cardiac and cardiac-related pathologies based on single-channel electrocardiogram analysis using artificial intelligence. To achieve this goal, a prospective, controlled, single-center, observational, non-randomized study will be conducted involving at least 4,000 patients meeting the inclusion criteria. All patients will undergo an expert echocardiography protocol with a comprehensive assessment of heart valve hemodynamics, systolic and diastolic myocardial function, along with standard measurements of the heart chambers and great vessels. To detect or exclude coronary artery disease: detection of significant coronary stenosis during coronary imaging: myocardial perfusion or determination of fractional coronary flow reserve, or stress echocardiography will be performed. For arterial hypertension: repeated blood pressure measurements in the office, 24-hour blood pressure monitoring will be performed. For cardiac arrhythmias: resting ECG and long-term Holter monitoring will be performed. For any cardiovascular pathology: blood tests: hemoglobin and red blood cell levels, glucose, glycated hemoglobin, oral glucose tolerance test, creatinine, uric acid, total cholesterol, low-density and high-density lipoproteins, and triglycerides will be performed. Additional testing data will be taken into account if conducted outside the protocol of this study. During the study, the authors will not interfere with the aforementioned scope of testing, which is performed on patients in accordance with clinical guidelines. All patients included in the study will undergo two ECG recordings in standard lead I for 1 minute, followed by spectral analysis of the obtained data, which will be stored at the remote monitoring center of Sechenov University without linking to the patients' personal data. A single-channel ECG will be recorded using a portable single-lead CardioQVARK ECG recorder. It was registered with the Federal Service for Surveillance in Healthcare on February 15, 2019. Number RU MI No. RZN 2024/22 855. The patient's personal data (last name, first name, patronymic, date of birth, contact information) will not be transferred or taken into account. Each patient is assigned an individual number that is not associated with his/her personal data. Then a spectral analysis of the electrocardiogram will be performed using a continuous wavelet transform, the principles of which are based on the Fourier transform. The analysis involves the evaluation of the following parameters (the parameters listed below will be calculated as the median of the tact-cycle):• TpTe - time from peak to end of the T-wave• VAT - time from the beginning of the QRS to the R-peak• QTc - corrected QT interval.• QT / TQ - the ratio of QT length to TQ length (from the end of T to the beginning of the QRS of the next complex).• QRS_E - the total energy of the QRS wave based on the wavelet transform• T_E - T-wave total energy based on wavelet transform• TP_E- energy of the main tooth of the T-wave based on the wavelet transform• BETA, BETA_S - T-wave asymmetry coefficients (simple and smooth versions)• BAD_T - flag of T-wave quality (whether expressed in the current lead• QRS_D1_ons - energy of the leading edge of the R-wave (based on the "first derivative" wavelet transform)• QRS_D1_offs - energy of the trailing edge of the R-wave (based on the "first derivative" wavelet transform)• QRS_D2 - peak energy of the R-wave (based on the "second derivative" wavelet transform)• QRS_Ei (i = 1,2,3,4) - QRS-wave energy in 4 frequency ranges (2-4-8-16-32 Hz) based on wavelet transform• T_Ei (i = 1,2,3,4) - T-wave energy in 4 frequency ranges (2-4-6-8-10 Hz) based on wavelet transform• HFQRS - the amplitude of the RF components of the QRS wave. Additionally used parameters:• TpTe, VAT, QTc - are duplicated to control the correctness of the record processing (the value of the UCC should be approximately equal to the median of the tick-by-bar).• QRSw - QRS width.• RA, SA, TA - the amplitudes of the R, S, T-waves, respectively, are used to normalize the parameters listed above.Statistical analysis and modeling will be performed using Python V3.8.8 and R V.4.0, as well as SPSS v.17.The correlation between various combinations of time, amplitude and frequency parameters of ECG and the presence of cardiac and cardiac-associated pathology will be analyzed. Certain parameters will be included in various multivariate analysis models: Lasso regression, Random Forest, Multilayer Perceptron, Support Vector Machine and Decision Tree. The model with the highest diagnostic accuracy will be selected, on which the algorithm will be tested.The outcome of this study will be the development and validation of an algorithm for identifying various cardiac and cardiac-associated pathologies based on the analysis of single-channel ECG parameters. The development of a medical-use program will also be undertaken.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Estimated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
4000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.

Study Contact Backup

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

All patients with or without cardiac and cardiac-associated pathologies over 18 years old

Description

Inclusion Criteria:

  1. The presence of written informed consent of the patient to participate in the study
  2. Availability of examination data allowing for the verification or exclusion of cardiac and cardiac-associated pathology
  3. Age 18 years old and older

Non-inclusion criteria:

  1. Patients with an implanted permanent pacemaker;
  2. ECG changes that prevent spectral analysis;
  3. Conditions that may impair the quality of the ECG recording (Parkinson's disease, essential tremor, etc.);
  4. Conditions that make ECG recording in lead I impossible (congenital anomalies of the upper limbs, traumatic amputation of the upper limbs).
  5. Lack of written informed consent from the patient to participate in the study.

Exclusion Criteria:

  1. Poor quality of the ECG recording on a single-channel ECG monitor
  2. Insufficient examination data to verify or exclude cardiac or cardiac-associated pathology;
  3. Patient's unwillingness to continue participating in the study for any reason.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
Training sample
2500 of patients 18 years old and older with and without cardiac and cardiac-associated pathology confirmed by the results of full examination (laboratory, clinical and instrumental) and by results of the spectral analysis of electrocardiogram (the parameters listed below will be calculated as the median of the tact-cycle: TpTe, VAT, QTc, QT / TQ, QRS_E, T_E, TP_E, BETA, BETA_S, BAD_T, QRS_D1_ons, QRS_D1_offs, QRS_D2, QRS_Ei (i = 1,2,3,4), T_Ei (i= 1,2,3,4), HFQRS, QRSw, RA, SA, TA and others).
Test sample
1500 of patients 18 years old and older with and without cardiac and cardiac-associated pathology confirmed by the results of full examination (laboratory, clinical and instrumental) and by results of the spectral analysis of electrocardiogram (the parameters listed below will be calculated as the median of the tact-cycle: TpTe, VAT, QTc, QT / TQ, QRS_E, T_E, TP_E, BETA, BETA_S, BAD_T, QRS_D1_ons, QRS_D1_offs, QRS_D2, QRS_Ei (i = 1,2,3,4), T_Ei (i= 1,2,3,4), HFQRS, QRSw, RA, SA, TA and others).

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
Parameters of single-channel ECG that significantly correlate with the presence of various cardiac and cardiac-associated pathologies
Time Frame: through study completion, an average of 2 years
comparison of the presence of cardiac and cardiac-associated pathology by the results of full examination (laboratory, clinical and instrumental) with the results of the presence of valvular heart defects obtained using the mathematical model of a single-channel ECG monitor
through study completion, an average of 2 years
Determination of sensitivity of various cardiac and cardiac-associated pathologies of multivariate models for analyzing single-channel electrocardiogram data
Time Frame: through study completion, an average of 2 years
comparison of the presence of cardiac and cardiac-associated pathology by the results of full examination (laboratory, clinical and instrumental) with the results of the presence of valvular heart defects obtained using the mathematical model of a single-channel ECG monitor
through study completion, an average of 2 years
Determination of specificity of various cardiac and cardiac-associated pathologies of multivariate models for analyzing single-channel electrocardiogram data
Time Frame: through study completion, an average of 2 years
comparison of the presence of cardiac and cardiac-associated pathology by the results of full examination (laboratory, clinical and instrumental) with the results of the presence of valvular heart defects obtained using the mathematical model of a single-channel ECG monitor
through study completion, an average of 2 years
Determination of diagnostic accuracy of various cardiac and cardiac-associated pathologies of multivariate models for analyzing single-channel electrocardiogram data
Time Frame: through study completion, an average of 2 years
comparison of the presence of cardiac and cardiac-associated pathology by the results of full examination (laboratory, clinical and instrumental) with the results of the presence of valvular heart defects obtained using the mathematical model of a single-channel ECG monitor
through study completion, an average of 2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
I.M. Sechenov First Moscow State Medical University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

  • A screening method for predicting left ventricular dysfunction based on spectral analysis of a single-channel electrocardiogram using machine learning algorithms / N. Kuznetsova, Zh. Sagirova, A. Suvorov [et al.] // Biomedical Signal Processing and Control. - 2023. - Vol. 86. - P. 105219. - DOI 10.1016/j.bspc.2023.105219. - EDN APQSQF.
  • Complex automated remote system for assessing hemodynamic parameters when analyzing the native signal of a single-channel ECG and pulse wave using machine learning techniques / N. O. Kuznetsova, Zh. N. Sagirova, E. A. Sultygova [et al.] // Russian Journal of Cardiology. - 2023. - T. 28, No. S7. - pp. 41-42. - EDN LZGDKG.
  • A Systematic Review on the Effectiveness of Machine Learning in the Detection of Atrial Fibrillation / A. L. Wuraola, B. Al-Dwa, D. Shchekochikhin [et al.] // Current Cardiology Reviews. - 2024. - Vol. 20. - DOI 10.2174/011573403x293703240715104503. - EDN XQZPAY.
  • A single-lead ECG based cardiotoxicity detection in patients on polychemotherapy / D. F. Mesitskaya, Z. Z. A. Fashafsha, M. G. Poltavskaya [et al.] // IJC Heart and Vasculature. - 2024. - Vol. 50. - P. 101336. - DOI 10.1016/j.ijcha.2024.101336. - EDN XMKKZY.
  • Kuznetsova N.O., Alekseeva A.M., Mamedzade F.E., Sedov V.P., Kopylov F.Yu., Syrkin A.L., Chomakhidze P.Sh. Screening for heart defects when analyzing an electrocardiogram using machine learning methods (literature review) // Bulletin of new medical technologies. Electronic edition. 2025. No. 1. Publication 1-6. DOI: 10.24412/2075-4094-2025-1-1-6. EDN KNFSNS
  • Kuznetsova N.O., Nartova A.A., Kurbanalieva N.K., Adueva D.Sh., Chursina E.Yu., Zhvania R.E., Ustinova D.I., Kostikova A.S., Kazakova M.V., Tarnaeva L.A., Chomakhidze P.Sh., Kopylov F.Yu. Results of screening for heart rhythm disturbances using a single-channel electrocardiogram without the participation of medical personnel // Bulletin of new medical technologies. 2025. No. 1. P. 56-60. DOI: 10.24412/1609-2163-2025-1-56-60. EDN YWJLFH.

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
April 1, 2026

Primary Completion (Estimated)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
March 1, 2028

Study Completion (Estimated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
May 13, 2028

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
February 2, 2026

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
February 2, 2026

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
February 9, 2026

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
April 16, 2026

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
April 13, 2026

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
April 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • 7747-211021

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

It is not possible to provide documentation due to the prohibition received from the local ethics committee

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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